Agentic AI Principal

Academic Key; Amsterdam; Remote; EUR 180,000 - 240,000; Full time

Job summary

Thoughtworks in Amsterdam seeks an Agentic AI Principal to act as the senior technical authority and trusted client advisor for enterprise agentic AI transformation across the DACH region. You will shape strategy, define agentic architectures and lead high-value C-suite engagements from opportunity through delivery.

With hands-on credibility in multi-agent systems, governance and safeguards, you will build a small, senior team and scale reusable patterns for regulated industries, delivering

Qualifications

• Senior-level authority with hands-on credibility in agentic AI and governance.
• Experience in complex enterprise AI transformations across regulated industries.
• Ability to lead C-suite engagements and shape architectures.

Responsibilities

• Shape and win Agentic AI advisory and strategy across DACH markets.
• Lead design of agentic architectures, orchestration, and compliance considerations.
• Guide complex programmes from opportunity through delivery and manage risk.
• Anchor agentic initiatives with product, data, and governance teams.

Skills

Agentic AI

Multi-agent systems

Governance and safeguards

C-suite engagement

Enterprise architecture

Tools

SAP S/4HANA

LIMS

QMS

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,

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Agentic AI Principal

thoughtworks · Amsterdam

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