Agentic AI Principal

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.