Senior Forward Deployed AI Engineer
The posting does not state a salary. This range is our estimate from the role, the location and the stack — treat it as a guide, not an offer.
- Level
- Senior
- Apply from
- United Kingdom
About the role
- Lead complex AI deployments end-to-end.
- Architect multi-agent solutions for clients.
- Design customized resource packs for AI.
- Mentor junior engineers on engagements.
- Drive intelligence loops and improvements.
Skills the posting asks for
- Python
- TypeScript
- JavaScript
- AI/ML
Summarised from the employer’s posting, which is reproduced in full below.
The employer’s full posting
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. You’ve 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. You think in platforms, not projects ,
- Strong written and verbal communication. Architecture documents, runbooks, strategic memos, training materials. Your Deployment Kits are your portfolio ,
- You leave teams better than you found them. You make sure the people you work with understand what was built, why it works, and how to own it without you ,
- Ability to travel. This role requires domestic and international travel approximately 25–50% of the time ,
- Elligible 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 of AI governance, ethics, and regulatory requirements (e.g. GDPR, UK/EU AI Act)
- 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, customize 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 personalized intelligence from the server so every connected AI surface gets smarter for that customer automatically ,
- Own Deployment Kit quality for your pod. If a kit is not documented well enough for a solutions consultant with no engineering background to follow, it isn’t done ,
- 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