Agentic AI Principal (m/f/d)

Free resume; Köln; Hybrid; EUR 180,000 - 260,000; Full time

Job summary

thoughtworks in Cologne, Germany is seeking an Agentic AI Principal to act as a senior technical authority and trusted client advisor for complex agentic AI transformation across the DACH region.

You will shape enterprise AI strategy and architecture, lead high-value C-suite engagements, and guide programmes from opportunity through delivery, with a focus on sovereign, compliant production-grade AI for healthcare and life sciences.

Qualifications

• Deep expertise in modern software engineering and Python; testing, CI/CD, observability, reliability.
• Experience architecting and delivering complex GenAI/agentic AI at enterprise scale.
• Knowledge of agentic architectures and frameworks (LangGraph, AutoGen, CrewAI, LlamaIndex); multi-agent coordination.
• Strong expertise in Retrieval-Augmented Generation and vector databases.
• Experience designing evaluation strategies for GenAI, including quality, safety, reliability, latency and cost.
• Understanding AI governance, safeguards, guardrails, responsible AI and secure deployment practices.

Responsibilities

• Shaping and winning: shape complex German/DACH pursuits, translating needs into propositions and architectures.
• Independently drive complex pursuits with executives, including commercial model considerations.
• Spar with C-suite buyers to frame business-outcome hypotheses and prove value quickly.
• Lead AI maturity assessments and align architecture to ROI.
• Represent Thoughtworks' agentic AI expertise in client conversations, forums and partnerships.
• Design and build architecture for production-grade agentic AI systems and enterprise integration.
• Integrate agents with SAP, LIMS, QMS, MES/PLM and other systems, using open protocols.
• Ensure data foundations with data teams; address data sovereignty and privacy.
• Guide production engineering, testing, CI/CD, reliability, cost and performance optimization.
• Provide leadership for complex programs; stay hands-on to validate architecture and manage risks.
• Partner with product, data, software, enterprise architecture, governance to deliver end-to-end solutions.
• Establish reusable patterns for observability, auditability, traceability and control of agentic systems.
• Translate EU AI Act obligations into engineering controls and evidence.
• Engage with works councils and officers; support DPIAs and co-determination processes.
• Anticipate governance challenges and define practical approaches for enterprise AI adoption.
• Set patterns and governance across teams; evolve Thoughtworks' agentic AI capability.
• Mentor engineers and grow the German team; raise AI fluency and standards.
• Evaluate emerging agentic AI technologies and guide responsible adoption.
• Build German and Dutch market presence through local-language perspectives and ecosystem initiatives.

Skills

Software engineering

GenAI

Agentic AI

Architectural design

Governance & safeguards

Tools

LangGraph

AutoGen

CrewAI

LlamaIndex

MCP

A2A

Job description

thoughtworks · Cologne, Germany · Posted 1d ago

Job Description

We are looking for an Agentic AI Principal to act as a senior technical authority and trusted client advisor for complex agentic AI transformation in Germany, the Netherlands and the wider DACH region.

Operating at Principal level, you will shape enterprise AI strategy, define agentic architecture blueprints, lead high-value C-suite engagements and guide complex programmes from opportunity through delivery. You will bring deep hands-on credibility in multi-agent systems, governance and safeguards, while setting reusable patterns and raising capability across teams.

The role has particular focus on sovereign, compliant and production-grade agentic AI for regulated German, Dutch and European enterprises, with a primary focus on healthcare and life sciences (pharma, biotech, medtech and healthcare providers). Experience from other regulated sectors, such as financial services and insurance, automotive and manufacturing, energy and telecommunications, is equally welcome.

Our delivery model is moving from large time-and-materials teams to small, AI-first, multidisciplinary pods accountable to a business outcome. You will anchor the agentic side of that work, pairing with our data, tech advisory and industry domain leads from presale through delivery.

This is a client-facing, builder's leadership role. You will start with a small, senior team and grow it through technical depth, delivery excellence and thought leadership, rather than inheriting a large organisation.

Job responsibilities

Shaping and winning

• Agentic AI advisory and strategy: shape and solution complex German, Dutch and DACH pursuits with account, commercial and delivery leaders, translating client needs into differentiated propositions, credible architectures and executable delivery approaches that support regional pipeline conversion.
• Independently drive complex pursuits with technical and executive stakeholders, including shaping the commercial model (fixed-price, outcome-linked), trade-offs and risk.
• Act as a sparring partner to C-suite buyers (CEO, CIO, CDO, CISO, COO): frame business-outcome hypotheses, challenge assumptions and define a thin slice of agentic delivery that proves value quickly.
• Lead AI maturity assessments, identify and prioritise processes for agentisation, and connect architecture choices to measurable business value and ROI.
• Represent Thoughtworks' agentic AI expertise in strategic client conversations, industry forums, partnerships and thought leadership where appropriate.

Designing and building

• Design and build engineering: set the architecture direction for complex, production-grade agentic AI systems, including multi-agent workflows, orchestration, tool use, memory, context strategy, retrieval, evaluation, observability and enterprise integration.
• Integrate agents with the German enterprise core: SAP (S/4HANA, BTP), LIMS, QMS and clinical systems, MES/PLM and industrial systems, and legacy back-office platforms, using open protocols such as MCP and A2A where they fit.
• Ensure agents run on trustworthy data foundations, working with data engineering and data product teams on data quality, semantics and access.
• Design solutions for regulated German and EU environments, with strong consideration of data sovereignty (EU and German sovereign cloud, open-weight or self-hosted models where required), privacy, security, responsible AI and applicable regulation, including the EU AI Act and GDPR; for healthcare and life sciences GxP, EU MDR/IVDR and the European Health Data Space; and for other sectors DORA, NIS2 and BaFin requirements where relevant.
• Guide teams in balancing rapid experimentation with robust production engineering, including evaluation-driven development, testing, CI/CD, reliability, cost and performance optimisation.
• Provide technical and delivery leadership for complex programmes, staying hands-on enough to validate architecture, unblock teams, manage technical risk and ensure successful execution.
• Partner with product, data, software engineering, enterprise architecture, governance and change specialists to design end-to-end solutions that deliver measurable business outcomes.

Governance and safeguards

• Establish reusable patterns for observability, auditability, traceability and control of agentic systems, enabling teams to demonstrate safe and reliable behaviour in production.
• Translate EU AI Act obligations (risk classification, human oversight, logging, technical documentation, GPAI-provider responsibilities) into concrete engineering controls and evidence.
• Engage early with works councils (Betriebsrat, ondernemingsraad), data protection officers and information security, supporting DPIAs and co-determination processes so agentic solutions that touch employee workflows can go live.
• Anticipate technical, organisational and governance challenges in enterprise AI adoption and define practical approaches to address them.

Principal-level leadership and growing capability

• Set reusable architecture patterns, engineering standards and governance practices across multiple teams and engagements, influencing the evolution of Thoughtworks' agentic AI capability beyond an individual programme.
• Set technical direction across multiple teams and initiatives, defining reusable patterns, frameworks and engineering standards for agentic AI delivery.
• Mentor senior engineers and technical leads, build the next generation of the German team, and raise AI fluency and agentic engineering standards across specialists and generalists.
• Evaluate emerging agentic AI technologies and frameworks and guide their responsible adoption based on client context, engineering quality and business value.
• Build our German and Dutch market presence through local-language points of view, ecosystem and partner initiatives (hyperscalers, SAP, European model providers) and community events.

Job qualifications

Technical Skills

• Deep expertise in modern software engineering and Python, with a strong track record of setting standards for testing, CI/CD, observability, maintainability and production reliability.
• Recognised experience architecting and delivering complex GenAI and agentic AI systems at enterprise scale, from early discovery through production deployment.
• Deep knowledge of agentic architectures and frameworks such as LangGraph, AutoGen, CrewAI, LlamaIndex or equivalent, including tool use, orchestration, memory, multi-agent coordination and interoperability protocols (MCP, A2A).
• Strong expertise in Retrieval-Augmented Generation, advanced information retrieval, vector databases and enterprise knowledge integration.
• Experience designing evaluation strategies for GenAI and agentic systems, including quality, safety, reliability, latency and cost measures.
• Strong understanding of AI governance and safeguards, including guardrails, red-team, observability, responsible AI and secure deployment practices (prompt injection, data leakage, tool misuse).
• Significant experience deploying AI systems on major cloud platforms using containers, orchestration and production-grade infrastructure patterns, including EU sovereign cloud, hybrid or on-premises setups and self-hosted open-weight models.
• Experience with model adaptation and optimisation techniques, includin