Senior Forward Deployed AI Engineer

Requirements:

• 6–10+ years production software engineering, including 3+ years deploying AI/ML to production.
• Deep Python; strong TypeScript/JavaScript.
• Proven track record leading complex enterprise technical engagements.
• Managed customer relationships, navigated security reviews, and delivered production systems organisations depend on.
• Deep production LLM experience: multi-agent orchestration, MCP/tool-use, RAG optimisation, evaluation frameworks, agent deployment at scale.
• System architecture expertise spanning enterprise systems, cloud infrastructure, and AI services explainable to a CIO and a junior engineer.
• Demonstrated ability to create reusable technical assets that others use in production.
• Strong written and verbal communication skills.
• Ability to travel approximately 25–50% of the time.
• Eligible to work in the UK on an ongoing basis.
• BS or MS in Computer Science, a related field, or equivalent industry experience (Desirable).
• Experience founding or scaling an FDE/solutions engineering function (Desirable).
• Technical founder background. Databricks, AWS Bedrock, or Temporal experience (Desirable).
• Deep domain knowledge in healthcare, financial services, or government.
• Agent framework contributions (Strands SDK, LangChain, open-source MCP servers) (Desirable).
• Proficiency in German/French language will be an added advantage (Desirable).
• Familiarity with AI governance, ethics, and regulatory requirements (e.g. GDPR, UK/EU AI Act).

What the job involves:

• Lead complex, multi-system AI deployments end-to-end: scope, architect, build, validate, and manage the customer relationship throughout.
• Own the AI workshop program for your pod, customise modules per customer, lead technical sessions, translate outputs into production requirements, evolve content from field learning.
• Architect multi-agent solutions selecting the right coordination pattern for each customer’s workflow characteristics and compliance requirements.
• Design client-specific and industry-specific MCP resource packs that serve personalised intelligence from the server so every connected AI surface gets smarter for that customer automatically.
• Own Deployment Kit quality for your pod.
• Lead Solutions Enablement Sprints: transfer AI deployment patterns to solutions consultants and partners with training materials and certification criteria.
• Drive the intelligence loop: author strategic memos, present field findings weekly, contribute Agent Bricks and Skills, file RFCs for platform improvements.
• Mentor junior FDEs on customer engagements, code reviews, and Deployment Kit quality.