Agentic AI Principal

Job responsibilities

• Agentic AI Advisory & Strategy: Shape and solution complex UKI pursuits, working with account, commercial and delivery leaders to translate client needs into differentiated propositions, credible architectures and executable delivery approaches that support regional pipeline conversion.
• Design & 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.
• Governance & Safeguards: Establish reusable patterns for observability, auditability, traceability and control of agentic systems, enabling teams to demonstrate safe and reliable behaviour in production.
• Principal-level leadership: 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.
• Design solutions appropriate for regulated UK environments, including financial services and telecommunications, with strong consideration of data sovereignty, privacy, security, responsible AI and applicable regulatory requirements.
• Provide technical and delivery leadership for complex programmes, maintaining sufficient hands-on involvement to validate architecture, unblock teams, manage technical risk and ensure successful execution.
• Set technical direction across multiple teams and initiatives, defining reusable patterns, frameworks and engineering standards for agentic AI delivery.
• Guide teams in balancing rapid experimentation with robust production engineering, including evaluation-driven development, testing, CI/CD, reliability, cost and performance optimisation.
• Partner with product, data, software engineering, enterprise architecture, governance and change specialists to design end-to-end solutions that deliver measurable business outcomes.
• Anticipate technical, organisational and governance challenges in enterprise AI adoption and define practical approaches to address them.
• Mentor senior engineers and technical leads, uplift broader engineering capability, and build confidence in agentic AI practices 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.
• Represent Thoughtworks' agentic AI expertise in strategic client conversations, industry forums, partnerships and thought leadership where appropriate.
• 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 and multi-t coordination patterns.
• 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-teaming, observability, responsible AI and secure deployment practices.
• Significant experience deploying AI systems on major cloud platforms using containers, orchestration and production-grade infrastructure patterns.
• Experience with model adaptation and optimisation techniques, including prompt/context engineering, fine-tuning where appropriate, and application-level performance optimisation.
• Ability to make sound architecture trade-offs across model capability, reliability, security, compliance, performance and cost.

Professional Skills

Learning & Development

Responsible Use of AI in Recruitment

About Thoughtworks

Qualifications

• 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 and multi-t coordination patterns.
• 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-teaming, observability, responsible AI and secure deployment practices.
• Significant experience deploying AI systems on major cloud platforms using containers, orchestration and production-grade infrastructure patterns.
• Experience with model adaptation and optimisation techniques, including prompt/context engineering, fine-tuning where appropriate, and application-level performance optimisation.
• Ability to make sound architecture trade-offs across model capability, reliability, security, compliance, performance and cost.
• Professional Skills
• Proven ability to lead C-suite and senior client engagements, rapidly establish credibility and advise on both business and technical choices.
• Strong consulting and commercial judgement, including experience shaping high-value opportunities, building investment cases and contributing directly to complex pipeline conversion.
• Ability to lead AI maturity assessments, identify and prioritise processes for agentization, and connect architecture choices to measurable business value and ROI.
• Executive presence and communication skills, with the ability to make complex agentic AI concepts, risks and trade-offs clear to technical and non-technical audiences.
• Proven leadership of complex delivery across multidisciplinary teams, with the ability to move fluidly between strategy, architecture, governance and hands-on technical leadership.
• Ability to influence across organisations without relying on formal authority, align diverse stakeholders and navigate ambiguity in high-value or high-risk programmes.
• Proven ability to mentor senior engineers and technical leaders and to raise standards and capability across a wider engineering community.
• Other things to know
• Learning & Development
• There is no one-size-fits-all career path at Thoughtworks: however you want to develop your career is entirely up to you. But we also balance autonomy with the strength of our cultivation culture. This means your career is supported by interactive tools, numerous development programs and teammates who want to help you grow. We see value in helping each other be our best and that extends to empowering our employees in their career journeys.
• Responsible Use of AI in Recruitment
• At Thoughtworks, we use AI tools to support our recruitment team with administrative tasks such as drafting communications, scheduling interviews and writing job descriptions.
• Crucially, our AI tools do not screen, assess, rank or make hiring decisions. Every application is reviewed by our team and all selection decisions are made exclusively by our interviewers and hiring managers.
• We are committed to fairness and responsible AI. We actively manage our AI systems by testing, monitoring for biased outcomes and implementing mitigation measures. We hold our third-party vendors to these same high standards through a rigorous governance process. For additional information, please see our full Thoughtworks AI Policy for Recruitment.