AI Architect | LLM Integration & Automation
Aktualisiert am 24.11.2025
Profil
Freiberufler / Selbstständiger
Remote-Arbeit
Verfügbar ab: 24.10.2025
Verfügbar zu: 100%
davon vor Ort: 100%
Bridging Strategy and Technology
Architecting Intelligent Systems
Driving Measurable Impact
Leading Through Change
Systemic Thinking & Vision
Data & AI Strategy
Digital Transformation
Automation
Agentic AI
LLMs
Process Optimization
Product & Change Management
Cloud Computing
User Empathy
Conversational AI
German
Muttersprache
English
Verhandlungssicher

Einsatzorte

Einsatzorte

Deutschland, Schweiz, Österreich
möglich

Projekte

Projekte

9 years 7 months
2016-05 - now

VP Product & Engineering

Co-Founder | Board member
Co-Founder | Board member
  • Building the Conversational AI platform for process and workflow automation.
  • Responsible for Product Management:
    • Product design and strategy, customer centric requierements analysis and translation between stakeholders, product definition, product innovation through integration of in-house developed/open source technologies enhancing customer satisfaction.
  • Responsible for Product Development & Engineering:
    • SaaS product architecture design and implementation/scaling, scalable infrastructure as code, software development life cycle, selecting technologies and managing tech stack, workpackage & task management, code reviews, run agile project management processes, improve product quality, security, & performance, testing.
  • Fundamental Technology Research:
    • Led technology innovation through cutting edge research projects from ideation, scoping to implementation, facilitation of write-up of research results and publishing with top tier research conferences such as ACL, CoNLL.
  • Recruitment & People Management:
    • Hired and managed cross functional teams of experts in the fields of ML engineering, linguists, and software engineers (including mobile; iOS & Android), hold regular 1:1s, draft quarterly OKRs and Engineering KPIs.
on request
London, UK
2 months
2025-08 - 2025-09

AI Use Case Discovery for Back-Office Process Automation

Agentic AI Process Automation Back-Office Optimization ...
Challenge:
  • The client?s back-office operations, covering document handling, customer data verification, and administrative workflows, relied heavily on manual processing.
  • Teams faced repetitive tasks, fragmented systems, and long turnaround times that limited scalability and efficiency. 
  • Leadership sought to explore how autonomous AI systems could autonomously coordinate, execute, and optimize internal processes to achieve higher operational efficiency and accuracy.

Approach:
  • Conducted a rapid AI opportunity assessment across core back-office workflows to identify automation and decision-support potential.
  • Mapped process bottlenecks and data dependencies across CRM, document
  • management, and compliance systems.
  • Designed and prioritized a set of agentic AI use cases, including automated document classification, information extraction, and workflow orchestration between departments.
  • Created a proof-of-concept architecture outlining how multi-agent AI systems could integrate with existing IT infrastructure while maintaining data privacy and regulatory
  • compliance.
  • Presented an AI adoption roadmap and value model quantifying expected ROI and effort for pilot implementation.

Results & Impact:
  • Identified four high-impact AI use cases capable of reducing manual workload by up to 65 %.
  • Delivered a blueprint for agentic process automation, setting the stage for pilot projects in document processing and data validation.
  • Enabled the client?s leadership team to prioritize AI investments based on quantifiable business value and compliance readiness.
Agentic AI Process Automation Back-Office Optimization Financial Services Document Automation AI Strategy Workflow Orchestration Data Compliance Digital Transformation
Leading German Financial Services Provider
1 year 9 months
2024-01 - 2025-09

Next Generation Multi-Agent AI Systems Development

Co-Founder & Chief Product & Technology Officer
Co-Founder & Chief Product & Technology Officer
  • Pioneering a new generation of AI by building the world?s most advanced Multi-Agent systems at scale. 
  • Our first series of Models will be aimed at revolutionising the supervised training and (inference) processes of LLMs and other neural networks, unlocking more powerful, efficient, cheaper, and safer Generative AI systems.
  • Ultimately, we aim to establish Inephany as a leading foundation models company, with particular expertise in models trained from the ground up, setting the stage for transformative advancements in AI.
on request
4 months
2025-02 - 2025-05

AI-Orchestrated Maintenance Automation from SCADA Systems

SCADA Predictive Maintenance Agentic AI ...
Challenge:
  • The client faced recurring equipment downtime and process inefficiencies in its production facilities. 
  • Maintenance operations were reactive, with manual SAP PM order creation, inconsistent task documentation, and frequent spare parts shortages. 
  • Although the client?s SCADA and historian systems captured detailed operational data, this information remained underutilized, preventing predictive and automated responses to critical alarms.

Approach:
  • Conducted a root-cause analysis of maintenance delays and data silos across SCADA, ERP, and historian systems.
  • Designed an AI-driven orchestration layer connecting SCADA alarms to standardized maintenance workflows.
  • Designed an agentic automation framework that:
  • Interprets SCADA alarms and maps them to pre-defined maintenance actions.
  • Automatically generates enriched SAP CM notifications and work orders, including spare parts suggestions.
  • Integrates data from historian and ERP systems to recommend procurement actions and prioritize critical repairs.
  • Uses human-in-the-loop review for low-confidence or high-cost events


Results & Impact:

  • Reduced unplanned downtime through faster and consistent maintenance response.
  • Automated SAP CM order creation, cutting manual effort and data entry time by over 70%.
  • Optimized spare parts management, minimizing SLA breaches and procurement delays.
  • Established a scalable AI orchestration blueprint for predictive and autonomous maintenance across multiple sites.
SCADA Predictive Maintenance Agentic AI Process Orchestration Industrial IoT SAP CM Integration Data-Driven Maintenance Workflow Automation Historian Data Operational Efficiency
Global Industrial Manufacturing & Energy Company (DAX)
2 years 4 months
2023-02 - 2025-05

Pilot Voice AI Solution for Remote Valve Inspection

Voice AI Field Operations Automation Process Digitization ...
Challenge:
  • A leading global energy company identified inefficiencies in its field operations: technicians were required to physically inspect valve handle positions across large sites to verify their state. 
  • Each inspection round took 10-15 minutes per valve, consuming valuable labor time and limiting data visibility across facilities. 
  • The client sought a digital, AI-driven method to check hundreds of valve statuses instantly through a mobile or voice interface.

Approach:
  • Conducted a process analysis and workflow mapping across field operations to identify inefficiencies.
  • Designed an AI-driven voice interface integrated with mobile and existing maintenance apps, enabling operators to query valve statuses instantly.
  • Developed a digital inspection data model to standardize and enrich asset data collection.
  • Facilitated cross-team workshops with Shell?s operations and data teams to align technical feasibility with field usability.


Results & Impact:

  • >90% reduction in operator inspection time (from 10?15 minutes to <10 seconds per check).
  • Significantly improved data accuracy and accessibility across maintenance and operations teams.
  • Laid the foundation for broader industrial workflow digitization and AI-assisted maintenance.
Voice AI Field Operations Automation Process Digitization Workflow Automation Data Capture Predictive Maintenance Industrial AI
Global Energy & Industrial Operations Company
7 months
2023-10 - 2024-04

Conversational AI Platform for Workflow Automation

Process Automation Conversational AI Efficiency Improvement ...
Challenge:
Manual form and inspection reporting was 4-7x slower and costlier than necessary due to
legacy tools and paper-based workflows - creating data gaps and productivity loss.

Approach:
  • Designed and delivered a digital transformation roadmap for form-based processes and billing workflows.
  • Defined and prioritized AI use cases across engineering and field departments.
  • Designed & built a mobile conversational AI and data platform integrating workflow automation and downstream billing.
  • Facilitated cross-functional workshops and led change adoption across departments.


Results & Impact:

  • 80 % reduction in reporting time per worker.
  • $1.6 M annual savings (scaling to $18 M projected).
  • Established an AI adoption and data governance framework ensuring sustainable rollout.
Process Automation Conversational AI Efficiency Improvement Digital Transformation Industry 4.0 Workflow Automation Digital Forms
Industrial & Construction Company Services (S&P 500)
4 months
2023-06 - 2023-09

AI Use Case Discovery & Process Automation for Offshore Operations

AI Use Case Discovery Process Automation Data Strategy ...
Challenge:
  • The client?s offshore drilling operations involved a multitude of manual, data-intensive workflows, from equipment inspections and maintenance scheduling to operational reporting and logistics coordination.
  • Key operational data was distributed across several legacy databases, limiting real-time visibility and process efficiency.
  • Leadership sought to identify AI use cases that could automate repetitive tasks, improve data accessibility, and enhance decision-making across engineering and field operations.

Approach:
  • Conducted an AI opportunity assessment across engineering and operations interfaces to identify high-impact automation and decision-support use cases.
  • Performed a data readiness analysis, mapping and prioritizing internal databases for integration into a unified automation layer.
  • Defined and validated a set of AI use cases, including conversational access to internal data, document automation, and automated quote generation workflows.
  • Designed a data-driven process automation roadmap, outlining required data pipelines, API integrations, and AI adoption milestones.
  • Facilitated stakeholder workshops with sales, IT, and business leaders to align priorities, quantify business value, and enable buy-in for AI-driven process change.


Results & Impact:

  • Identified and validated five scalable AI use cases with measurable ROI potential.Designed a blueprint for data-driven automation, reducing manual search and reporting efforts by up to 70%.
  • Enabled cross-departmental alignment through shared process KPIs and AI-readiness workshops.
  • Established the foundation for a conversational AI layer to streamline access to internal knowledge assets and support future LLM integration.
AI Use Case Discovery Process Automation Data Strategy Workflow Optimization Conversational AI Data Integration LLM Readiness Digital Transformation
Global Energy Technology & Industrial Services Company (S&P 500)
6 months
2022-01 - 2022-06

Context-Aware Conversational Infotainment System

Conversational AI Automotive Infotainment Agentic Systems ...
Challenge:
  • Modern in-car assistants (Alexa, Google Assistant, proprietary OEM solutions) operate in silos, they respond to isolated commands but fail to maintain conversational or situational context. 
  • Drivers often need to remember exact phrasing or commands to control vehicle functions or access information. 
  • The client sought to design a unified conversational AI architecture capable of understanding user intent, maintaining context across multiple interactions, and enabling natural dialogue without repetitive instructions.

Approach:
  • Conducted a use case and user intent analysis to identify key conversational pain points and desired interactions.
  • Designed an AI architecture combining third-party voice ecosystems (Alexa, Google, proprietary Bosch functions) via a unified function-calling interface.
  • Defined the data and API strategy for function call translation, enabling cross-system command execution from a single conversational layer.
  • Developed a memory and discourse model (?DiscourseModel?).

Results & Impact:
  • Designed a context-aware conversational AI framework that delivers a natural,
  • human-like interaction experience.
  • Reduced user friction by eliminating the need for memorized commands (?I just talk naturally to my car?).
  • Created a scalable function-calling and memory model architecture now serving as the foundation for next-generation infotainment systems.
  • Established design principles for agentic in-car assistants capable of proactive, multi-turn, and cross-domain interactions.
Conversational AI Automotive Infotainment Agentic Systems Function Calling Context Memory Dialogue Management Voice Assistants UX for AI Discourse Model AI Product Strategy
1-Tier Supplier Automotive
1 year 6 months
2014-11 - 2016-04

SW and infrastructure requirements

IT-Consultant
IT-Consultant
  • Analysed functional and technical SW and infrastructure requirements
  • Analysed sw conditions as scalability, performance and maintainability
  • Close cooperation with sw architects/developers, PM re plan, build and run
  • Ensured a complete and adequate documentation to serve all relevant stakeholders
  • Assured a detailed requirements/architectural documentation produced by development teams
Lufthansa Industrie Solutions GmbH, Hamburg, Germany
5 months
2014-06 - 2014-10

IT Project Management

  • Planning, implementing and monitoring projects with respect to costs & deadlines
  • Responsibility of PM areas, such as scope, risk, release and change
  • Ensured compliance with defined development processes and governance
  • Took on responsibility for internal service units that supply software components
  • Engaged in dialog and managing relationships with internal and external project stakeholders
  • Compiled necessary reports and documentation
Lufthansa Systems AG, Frankfurt, Germany
5 months
2014-06 - 2014-10

Product Management / Business Process Optimization

  • Analysing, Mapping and modelling of process landscapes
  • Optimised processes along the overhauling supply chain
  • Project controlling
  • Data warehouse integration as controlling and reporting instrument
Lufthansa Technik AG, Munich, Germany

Aus- und Weiterbildung

Aus- und Weiterbildung

Certifications
  • Certified Scrum Product Owner
  • Microsoft AI Product Manager
  • NVIDIA Inception Program
  • Plug & Play Mobility
  • AWS GenAI Accelerator

Position

Position

  • Founder
  • AI Product Manager & Digital Transformation Expert
  • Automation
  • Data & AI Strategy

Kompetenzen

Kompetenzen

Top-Skills

Bridging Strategy and Technology Architecting Intelligent Systems Driving Measurable Impact Leading Through Change Systemic Thinking & Vision Data & AI Strategy Digital Transformation Automation Agentic AI LLMs Process Optimization Product & Change Management Cloud Computing User Empathy Conversational AI

Produkte / Standards / Erfahrungen / Methoden

Profile

  • I help organizations break down silos and accelerate transformation through automation, data, and AI. I deliver a continuous, data-driven model that combines strategy, platform development, and change enablement to build lasting digital maturity
  • My work focuses on connecting strategy, technology, and execution to turn complex transformation goals into measurable results. Core Expertise:
    • Digital transformation & product strategy
    • Data architecture modernization, predictive analytics, LLMs & agentic systems
    • API-first platforms, workflow automation & system integration
    • AI-driven business model innovation & rapid prototyping
    • Agile organization design, team enablement & leadership coaching
  • With a background spanning consulting, AI product management, and agile delivery, I bridge business and technology to create adaptive, innovation-ready organizations. Clients include startups, mid-sized firms, and global enterprises (S&P 500, DAX) across technology, professional services, and industry.


SKILLS

Strategic & Business

  • Business acumen, ideation & creative thinking, change management, innovation leadership, strategic visioning & planning, project & stakeholder management, automation, AI governance, market & data analysis, negotiation, user empathy.
  • Venture capital raised +8M in $ to date.


Technical

  • AI & ML:
    • Deep understanding of AI and ML principles, algorithms, and frameworks. Ability to develop, implement, and evaluate machine learning models.
  • Data Science and Analytics:
    • Expertise in data collection, preprocessing, analysis, and visualization. Proficiency in statistical methods and data-driven decision making.
  • Programming and Software Development:
    • Proficiency in programming languages such as Python, Javascript. Familiarity with software development practices and tools.
  • Cloud Computing:
    • Knowledge of cloud platforms for deploying and scaling AI solutions.
  • Big Data Technologies:
    • Understanding of big data ecosystems and data management systems
  • AI Ethics and Governance:
    • Awareness of ethical considerations, bias mitigation, and governance frameworks in AI implementation.


Interpersonal

Adaptability, communication, problem-solving, collaboration, leadership, ethical judgement


Continuous learning

Commitment to staying updated with the latest advancements in AI, ML, and related technologies.


TECHNOLOGIES & TOOLS

  • ASR/TTS - Whisper, Riva, Speechmatics, custom lexicon & configuration
  • NLP - LLMS (OpenAI, Google, Meta, Anthropic), Prompt engineering, LLM frameworks (e.g. LangChain, Guidance, Llamaindex, Huggingface)
  • RAG - Q&A, Search, chatbots, summarization, information retrieval recommender systems
  • Data stores - Vector stores (e.g. Milvus), SQL, NOSQL
  • Data Eng - ETL, feature engineering, large datasets (Hadoop, Kafka, Spark) Grafana
  • Cloud platforms - AWS, Google Cloud, Azure, Lambda, FlexAI,
  • Agile/PM - Kanban, Jira, Confluence, SCRUM, Backlog Management, Figma, Notion, Asana, Trello, Slack, Microsoft Teams
  • Software Dev - APIs (REST, Postman, Swagger) Python, Java, Javascript, HTML, Docker, Code review, A/B Testing (VWO), Figma
  • ML dev platforms - Weights & Biases, MLflow
  • Compliance - Platforms (Drata and Vanta), SOC-2 and ISO 27001 standards, GDPR
  • Automation & Data Ops - Airflow Zapier, Make, n8n
  • AI coding tools - OpenAI Codex, Claude, Google Gemini, Github/Microsoft Copilot, Windsur


Work Experience

Customer: on request


Tasks:

  • A venture-backed deep tech company building future-proof AI solutions in Industry Classification, Risk Factor Models, and Portfolio Analysis for the global finance and investment arenas.
  • Guidance of product-tech alignement, participating in product feature design, liaison between product and engineering teams. Lead development implementation, and integration of various elements of IP for clients.
  • Advising early-stage startups on company formation, fundraising strategy, GTM and product?market fit, leveraging experience from multiple successful ventures.


Role: Partner

Customer: on request


Tasks:

  • A boutique digital transformation firm specializing in unifying organizational silos through automation, data, and AI [by request] delivers Transformation as a Service (TaaS), a continuous, data-driven approach that combines strategy, platform development, and change enablement.
  • Focused on measurable outcomes, modern architectures and agile execution, the firm helps mid-sized and enterprise clients accelerate digital maturity and build lasting product and data capabilities

Programmiersprachen

Python
Javascript

Einsatzorte

Einsatzorte

Deutschland, Schweiz, Österreich
möglich

Projekte

Projekte

9 years 7 months
2016-05 - now

VP Product & Engineering

Co-Founder | Board member
Co-Founder | Board member
  • Building the Conversational AI platform for process and workflow automation.
  • Responsible for Product Management:
    • Product design and strategy, customer centric requierements analysis and translation between stakeholders, product definition, product innovation through integration of in-house developed/open source technologies enhancing customer satisfaction.
  • Responsible for Product Development & Engineering:
    • SaaS product architecture design and implementation/scaling, scalable infrastructure as code, software development life cycle, selecting technologies and managing tech stack, workpackage & task management, code reviews, run agile project management processes, improve product quality, security, & performance, testing.
  • Fundamental Technology Research:
    • Led technology innovation through cutting edge research projects from ideation, scoping to implementation, facilitation of write-up of research results and publishing with top tier research conferences such as ACL, CoNLL.
  • Recruitment & People Management:
    • Hired and managed cross functional teams of experts in the fields of ML engineering, linguists, and software engineers (including mobile; iOS & Android), hold regular 1:1s, draft quarterly OKRs and Engineering KPIs.
on request
London, UK
2 months
2025-08 - 2025-09

AI Use Case Discovery for Back-Office Process Automation

Agentic AI Process Automation Back-Office Optimization ...
Challenge:
  • The client?s back-office operations, covering document handling, customer data verification, and administrative workflows, relied heavily on manual processing.
  • Teams faced repetitive tasks, fragmented systems, and long turnaround times that limited scalability and efficiency. 
  • Leadership sought to explore how autonomous AI systems could autonomously coordinate, execute, and optimize internal processes to achieve higher operational efficiency and accuracy.

Approach:
  • Conducted a rapid AI opportunity assessment across core back-office workflows to identify automation and decision-support potential.
  • Mapped process bottlenecks and data dependencies across CRM, document
  • management, and compliance systems.
  • Designed and prioritized a set of agentic AI use cases, including automated document classification, information extraction, and workflow orchestration between departments.
  • Created a proof-of-concept architecture outlining how multi-agent AI systems could integrate with existing IT infrastructure while maintaining data privacy and regulatory
  • compliance.
  • Presented an AI adoption roadmap and value model quantifying expected ROI and effort for pilot implementation.

Results & Impact:
  • Identified four high-impact AI use cases capable of reducing manual workload by up to 65 %.
  • Delivered a blueprint for agentic process automation, setting the stage for pilot projects in document processing and data validation.
  • Enabled the client?s leadership team to prioritize AI investments based on quantifiable business value and compliance readiness.
Agentic AI Process Automation Back-Office Optimization Financial Services Document Automation AI Strategy Workflow Orchestration Data Compliance Digital Transformation
Leading German Financial Services Provider
1 year 9 months
2024-01 - 2025-09

Next Generation Multi-Agent AI Systems Development

Co-Founder & Chief Product & Technology Officer
Co-Founder & Chief Product & Technology Officer
  • Pioneering a new generation of AI by building the world?s most advanced Multi-Agent systems at scale. 
  • Our first series of Models will be aimed at revolutionising the supervised training and (inference) processes of LLMs and other neural networks, unlocking more powerful, efficient, cheaper, and safer Generative AI systems.
  • Ultimately, we aim to establish Inephany as a leading foundation models company, with particular expertise in models trained from the ground up, setting the stage for transformative advancements in AI.
on request
4 months
2025-02 - 2025-05

AI-Orchestrated Maintenance Automation from SCADA Systems

SCADA Predictive Maintenance Agentic AI ...
Challenge:
  • The client faced recurring equipment downtime and process inefficiencies in its production facilities. 
  • Maintenance operations were reactive, with manual SAP PM order creation, inconsistent task documentation, and frequent spare parts shortages. 
  • Although the client?s SCADA and historian systems captured detailed operational data, this information remained underutilized, preventing predictive and automated responses to critical alarms.

Approach:
  • Conducted a root-cause analysis of maintenance delays and data silos across SCADA, ERP, and historian systems.
  • Designed an AI-driven orchestration layer connecting SCADA alarms to standardized maintenance workflows.
  • Designed an agentic automation framework that:
  • Interprets SCADA alarms and maps them to pre-defined maintenance actions.
  • Automatically generates enriched SAP CM notifications and work orders, including spare parts suggestions.
  • Integrates data from historian and ERP systems to recommend procurement actions and prioritize critical repairs.
  • Uses human-in-the-loop review for low-confidence or high-cost events


Results & Impact:

  • Reduced unplanned downtime through faster and consistent maintenance response.
  • Automated SAP CM order creation, cutting manual effort and data entry time by over 70%.
  • Optimized spare parts management, minimizing SLA breaches and procurement delays.
  • Established a scalable AI orchestration blueprint for predictive and autonomous maintenance across multiple sites.
SCADA Predictive Maintenance Agentic AI Process Orchestration Industrial IoT SAP CM Integration Data-Driven Maintenance Workflow Automation Historian Data Operational Efficiency
Global Industrial Manufacturing & Energy Company (DAX)
2 years 4 months
2023-02 - 2025-05

Pilot Voice AI Solution for Remote Valve Inspection

Voice AI Field Operations Automation Process Digitization ...
Challenge:
  • A leading global energy company identified inefficiencies in its field operations: technicians were required to physically inspect valve handle positions across large sites to verify their state. 
  • Each inspection round took 10-15 minutes per valve, consuming valuable labor time and limiting data visibility across facilities. 
  • The client sought a digital, AI-driven method to check hundreds of valve statuses instantly through a mobile or voice interface.

Approach:
  • Conducted a process analysis and workflow mapping across field operations to identify inefficiencies.
  • Designed an AI-driven voice interface integrated with mobile and existing maintenance apps, enabling operators to query valve statuses instantly.
  • Developed a digital inspection data model to standardize and enrich asset data collection.
  • Facilitated cross-team workshops with Shell?s operations and data teams to align technical feasibility with field usability.


Results & Impact:

  • >90% reduction in operator inspection time (from 10?15 minutes to <10 seconds per check).
  • Significantly improved data accuracy and accessibility across maintenance and operations teams.
  • Laid the foundation for broader industrial workflow digitization and AI-assisted maintenance.
Voice AI Field Operations Automation Process Digitization Workflow Automation Data Capture Predictive Maintenance Industrial AI
Global Energy & Industrial Operations Company
7 months
2023-10 - 2024-04

Conversational AI Platform for Workflow Automation

Process Automation Conversational AI Efficiency Improvement ...
Challenge:
Manual form and inspection reporting was 4-7x slower and costlier than necessary due to
legacy tools and paper-based workflows - creating data gaps and productivity loss.

Approach:
  • Designed and delivered a digital transformation roadmap for form-based processes and billing workflows.
  • Defined and prioritized AI use cases across engineering and field departments.
  • Designed & built a mobile conversational AI and data platform integrating workflow automation and downstream billing.
  • Facilitated cross-functional workshops and led change adoption across departments.


Results & Impact:

  • 80 % reduction in reporting time per worker.
  • $1.6 M annual savings (scaling to $18 M projected).
  • Established an AI adoption and data governance framework ensuring sustainable rollout.
Process Automation Conversational AI Efficiency Improvement Digital Transformation Industry 4.0 Workflow Automation Digital Forms
Industrial & Construction Company Services (S&P 500)
4 months
2023-06 - 2023-09

AI Use Case Discovery & Process Automation for Offshore Operations

AI Use Case Discovery Process Automation Data Strategy ...
Challenge:
  • The client?s offshore drilling operations involved a multitude of manual, data-intensive workflows, from equipment inspections and maintenance scheduling to operational reporting and logistics coordination.
  • Key operational data was distributed across several legacy databases, limiting real-time visibility and process efficiency.
  • Leadership sought to identify AI use cases that could automate repetitive tasks, improve data accessibility, and enhance decision-making across engineering and field operations.

Approach:
  • Conducted an AI opportunity assessment across engineering and operations interfaces to identify high-impact automation and decision-support use cases.
  • Performed a data readiness analysis, mapping and prioritizing internal databases for integration into a unified automation layer.
  • Defined and validated a set of AI use cases, including conversational access to internal data, document automation, and automated quote generation workflows.
  • Designed a data-driven process automation roadmap, outlining required data pipelines, API integrations, and AI adoption milestones.
  • Facilitated stakeholder workshops with sales, IT, and business leaders to align priorities, quantify business value, and enable buy-in for AI-driven process change.


Results & Impact:

  • Identified and validated five scalable AI use cases with measurable ROI potential.Designed a blueprint for data-driven automation, reducing manual search and reporting efforts by up to 70%.
  • Enabled cross-departmental alignment through shared process KPIs and AI-readiness workshops.
  • Established the foundation for a conversational AI layer to streamline access to internal knowledge assets and support future LLM integration.
AI Use Case Discovery Process Automation Data Strategy Workflow Optimization Conversational AI Data Integration LLM Readiness Digital Transformation
Global Energy Technology & Industrial Services Company (S&P 500)
6 months
2022-01 - 2022-06

Context-Aware Conversational Infotainment System

Conversational AI Automotive Infotainment Agentic Systems ...
Challenge:
  • Modern in-car assistants (Alexa, Google Assistant, proprietary OEM solutions) operate in silos, they respond to isolated commands but fail to maintain conversational or situational context. 
  • Drivers often need to remember exact phrasing or commands to control vehicle functions or access information. 
  • The client sought to design a unified conversational AI architecture capable of understanding user intent, maintaining context across multiple interactions, and enabling natural dialogue without repetitive instructions.

Approach:
  • Conducted a use case and user intent analysis to identify key conversational pain points and desired interactions.
  • Designed an AI architecture combining third-party voice ecosystems (Alexa, Google, proprietary Bosch functions) via a unified function-calling interface.
  • Defined the data and API strategy for function call translation, enabling cross-system command execution from a single conversational layer.
  • Developed a memory and discourse model (?DiscourseModel?).

Results & Impact:
  • Designed a context-aware conversational AI framework that delivers a natural,
  • human-like interaction experience.
  • Reduced user friction by eliminating the need for memorized commands (?I just talk naturally to my car?).
  • Created a scalable function-calling and memory model architecture now serving as the foundation for next-generation infotainment systems.
  • Established design principles for agentic in-car assistants capable of proactive, multi-turn, and cross-domain interactions.
Conversational AI Automotive Infotainment Agentic Systems Function Calling Context Memory Dialogue Management Voice Assistants UX for AI Discourse Model AI Product Strategy
1-Tier Supplier Automotive
1 year 6 months
2014-11 - 2016-04

SW and infrastructure requirements

IT-Consultant
IT-Consultant
  • Analysed functional and technical SW and infrastructure requirements
  • Analysed sw conditions as scalability, performance and maintainability
  • Close cooperation with sw architects/developers, PM re plan, build and run
  • Ensured a complete and adequate documentation to serve all relevant stakeholders
  • Assured a detailed requirements/architectural documentation produced by development teams
Lufthansa Industrie Solutions GmbH, Hamburg, Germany
5 months
2014-06 - 2014-10

IT Project Management

  • Planning, implementing and monitoring projects with respect to costs & deadlines
  • Responsibility of PM areas, such as scope, risk, release and change
  • Ensured compliance with defined development processes and governance
  • Took on responsibility for internal service units that supply software components
  • Engaged in dialog and managing relationships with internal and external project stakeholders
  • Compiled necessary reports and documentation
Lufthansa Systems AG, Frankfurt, Germany
5 months
2014-06 - 2014-10

Product Management / Business Process Optimization

  • Analysing, Mapping and modelling of process landscapes
  • Optimised processes along the overhauling supply chain
  • Project controlling
  • Data warehouse integration as controlling and reporting instrument
Lufthansa Technik AG, Munich, Germany

Aus- und Weiterbildung

Aus- und Weiterbildung

Certifications
  • Certified Scrum Product Owner
  • Microsoft AI Product Manager
  • NVIDIA Inception Program
  • Plug & Play Mobility
  • AWS GenAI Accelerator

Position

Position

  • Founder
  • AI Product Manager & Digital Transformation Expert
  • Automation
  • Data & AI Strategy

Kompetenzen

Kompetenzen

Top-Skills

Bridging Strategy and Technology Architecting Intelligent Systems Driving Measurable Impact Leading Through Change Systemic Thinking & Vision Data & AI Strategy Digital Transformation Automation Agentic AI LLMs Process Optimization Product & Change Management Cloud Computing User Empathy Conversational AI

Produkte / Standards / Erfahrungen / Methoden

Profile

  • I help organizations break down silos and accelerate transformation through automation, data, and AI. I deliver a continuous, data-driven model that combines strategy, platform development, and change enablement to build lasting digital maturity
  • My work focuses on connecting strategy, technology, and execution to turn complex transformation goals into measurable results. Core Expertise:
    • Digital transformation & product strategy
    • Data architecture modernization, predictive analytics, LLMs & agentic systems
    • API-first platforms, workflow automation & system integration
    • AI-driven business model innovation & rapid prototyping
    • Agile organization design, team enablement & leadership coaching
  • With a background spanning consulting, AI product management, and agile delivery, I bridge business and technology to create adaptive, innovation-ready organizations. Clients include startups, mid-sized firms, and global enterprises (S&P 500, DAX) across technology, professional services, and industry.


SKILLS

Strategic & Business

  • Business acumen, ideation & creative thinking, change management, innovation leadership, strategic visioning & planning, project & stakeholder management, automation, AI governance, market & data analysis, negotiation, user empathy.
  • Venture capital raised +8M in $ to date.


Technical

  • AI & ML:
    • Deep understanding of AI and ML principles, algorithms, and frameworks. Ability to develop, implement, and evaluate machine learning models.
  • Data Science and Analytics:
    • Expertise in data collection, preprocessing, analysis, and visualization. Proficiency in statistical methods and data-driven decision making.
  • Programming and Software Development:
    • Proficiency in programming languages such as Python, Javascript. Familiarity with software development practices and tools.
  • Cloud Computing:
    • Knowledge of cloud platforms for deploying and scaling AI solutions.
  • Big Data Technologies:
    • Understanding of big data ecosystems and data management systems
  • AI Ethics and Governance:
    • Awareness of ethical considerations, bias mitigation, and governance frameworks in AI implementation.


Interpersonal

Adaptability, communication, problem-solving, collaboration, leadership, ethical judgement


Continuous learning

Commitment to staying updated with the latest advancements in AI, ML, and related technologies.


TECHNOLOGIES & TOOLS

  • ASR/TTS - Whisper, Riva, Speechmatics, custom lexicon & configuration
  • NLP - LLMS (OpenAI, Google, Meta, Anthropic), Prompt engineering, LLM frameworks (e.g. LangChain, Guidance, Llamaindex, Huggingface)
  • RAG - Q&A, Search, chatbots, summarization, information retrieval recommender systems
  • Data stores - Vector stores (e.g. Milvus), SQL, NOSQL
  • Data Eng - ETL, feature engineering, large datasets (Hadoop, Kafka, Spark) Grafana
  • Cloud platforms - AWS, Google Cloud, Azure, Lambda, FlexAI,
  • Agile/PM - Kanban, Jira, Confluence, SCRUM, Backlog Management, Figma, Notion, Asana, Trello, Slack, Microsoft Teams
  • Software Dev - APIs (REST, Postman, Swagger) Python, Java, Javascript, HTML, Docker, Code review, A/B Testing (VWO), Figma
  • ML dev platforms - Weights & Biases, MLflow
  • Compliance - Platforms (Drata and Vanta), SOC-2 and ISO 27001 standards, GDPR
  • Automation & Data Ops - Airflow Zapier, Make, n8n
  • AI coding tools - OpenAI Codex, Claude, Google Gemini, Github/Microsoft Copilot, Windsur


Work Experience

Customer: on request


Tasks:

  • A venture-backed deep tech company building future-proof AI solutions in Industry Classification, Risk Factor Models, and Portfolio Analysis for the global finance and investment arenas.
  • Guidance of product-tech alignement, participating in product feature design, liaison between product and engineering teams. Lead development implementation, and integration of various elements of IP for clients.
  • Advising early-stage startups on company formation, fundraising strategy, GTM and product?market fit, leveraging experience from multiple successful ventures.


Role: Partner

Customer: on request


Tasks:

  • A boutique digital transformation firm specializing in unifying organizational silos through automation, data, and AI [by request] delivers Transformation as a Service (TaaS), a continuous, data-driven approach that combines strategy, platform development, and change enablement.
  • Focused on measurable outcomes, modern architectures and agile execution, the firm helps mid-sized and enterprise clients accelerate digital maturity and build lasting product and data capabilities

Programmiersprachen

Python
Javascript

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