Lead AI Engineer

We are looking for a passionate and skilled AI engineer to lead the AI engineering practice at a team or program level. In this role, you will guide the design and delivery of generative AI solutions, shape the technical roadmap for your team(s), and ensure high standards of engineering excellence. You will provide technical leadership to a small group of engineers, collaborate with product and business partners, and act as a trusted technical consultant for stakeholders. Job responsibilities Lead a cross-functional team of software engineers, data scientists and other specialists delivering GenAI solutions. Guide the design and delivery of AI-powered systems that are scalable, reliable and production-ready. Set direction for technical decisions, ensuring AI solutions are optimized for performance, cost and maintainability. Collaborate closely with product managers, designers and stakeholders to align technical solutions with business goals. Establish and promote best practices in AI engineering, covering testing, guardrails, responsible AI, monitoring and documentation, while uplifting the team by sharing knowledge, tools and practices that enable both SMEs and generalists to contribute effectively. Provide architectural guidance, balancing experimentation with delivery in short, safe cycles. Review designs and code across the team, ensuring quality and consistency in AI-enabled features. Set direction for GenAI application optimization to improve accuracy, performance, cost and know when model tuning is required. Job qualifications Technical Skills Strong expertise in Python and modern software engineering practices, including CI/CD, testing, version control and system reliability. Proven ability to design and integrate end-to-end AI systems, ensuring scalability, maintainability and performance. Deep experience with GenAI and agentic frameworks, guiding teams in their effective use. Expertise in building and scaling RAG pipelines and integrating vector databases into production systems. Experience deploying AI solutions on major cloud platforms, using containers and CI/CD pipelines for reproducibility. Skilled in LLMOps practices and monitoring production systems with observability tools. Experience with fine-tuning, model adaptation and advanced use of ML/NLP frameworks. Professional Skills Ability to articulate complex technical concepts to non-technical audiences and influence senior decision-makers. Proven ability to inspire, mentor and develop high-performing engineering teams, fostering a collaborative and inclusive environment. Demonstrates the ability to anticipate technological trends and proactively shape the technical direction of the team. Skilled in navigating complex internal and external dynamics, driving consensus and achieving technical and business goals. 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 proces…