Forward Deployed Engineer

The role

As a Forward Deployed Engineer, you embed with a client team and own getting an AI use case from idea to production. You’re the engineer who sits closest to the problem: you scope it, build it, ship it and make sure it sticks.

Location:

Remote within EU nearshore regions

What you’ll do

Specify

• Work directly with client stakeholders to find the AI use cases worth building, and the ones that aren’t.
• Turn vague business problems into scoped, measurable deliverables with clear success criteria.
• Assess data readiness, integration points and constraints before anything is built.

Execute

• Build production-grade solutions hands-on: LLM integrations, agents, retrieval pipelines, data plumbing and the services around them.
• Lead and direct your Remobi nearshore pod, splitting work and reviewing their output.
• Ship in short cycles and show working software early.

Authorise

• Take solutions through client security, compliance and governance review.
• Put evaluation, monitoring and guardrails in place so the client can trust what goes live.

Sustain

• Hand over cleanly: documentation, runbooks and knowledge transfer to client teams.
• Spot the next problem worth solving and bring it back to Remobi as an expansion opportunity.
• Feed what you learn back into NAOS and the wider Remobi community.

What you’ll bring

• 6+ years building and shipping production software, with strong Python and/or TypeScript.
• Solid full-stack range: APIs, data pipelines, cloud infrastructure (AWS, Azure or GCP) and CI/CD.
• Comfort working in messy, real enterprise environments: legacy systems, tight security, imperfect data.

Applied AI

• Hands-on experience putting LLM-based solutions into production, not just prototypes.
• Working knowledge of retrieval (RAG), tool use and agents, prompt design and model evaluation.
• Experience with at least one major model provider’s API (Anthropic, OpenAI or similar).

Consulting

• You can sit with a non-technical stakeholder, understand what they actually need, and say no when you should.
• Clear written and spoken English; you can explain trade-offs to an engineer and an executive in the same day.
• You own outcomes. When something is blocked, you unblock it.
• Experience leading or mentoring a small team of engineers.

Nice to have

• Background in a client-facing engineering role: consultancy, solutions engineering or a previous FDE position.
• Experience in regulated or industrial sectors such as energy, manufacturing or financial services.
• Knowledge graphs, semantic data or enterprise search.
• Experience with Claude and the Anthropic platform.
• Fluency in a second European language.

How you’ll be measured

• Outcomes shipped: AI use cases live in production against agreed success criteria.
• Client trust: stakeholder satisfaction and repeat requests for your involvement.
• Account growth: follow-on work and pod headcount generated from your engagements.
• Pod delivery: quality and pace of the nearshore team you lead.
• Contribution: improvements you bring back to our NAOS Framework and the Remobi community.

• 6+ years building and shipping production software, with strong Python and/or TypeScript.
• Solid full-stack range: APIs, data pipelines, cloud infrastructure (AWS, Azure or GCP) and CI/CD.
• Comfort working in messy, real enterprise environments: legacy systems, tight security, imperfect data.

Applied AI

• Hands-on experience putting LLM-based solutions into production, not just prototypes.
• Working knowledge of retrieval (RAG), tool use and agents, prompt design and model evaluation.
• Experience with at least one major model provider’s API (Anthropic, OpenAI or similar).

Consulting

• You can sit with a non-technical stakeholder, understand what they actually need, and say no when you should.
• Clear written and spoken English; you can explain trade-offs to an engineer and an executive in the same day.
• You own outcomes. When something is blocked, you unblock it.
• Experience leading or mentoring a small team of engineers.

Nice to have

• Background in a client-facing engineering role: consultancy, solutions engineering or a previous FDE position.
• Experience in regulated or industrial sectors such as energy, manufacturing or financial services.
• Knowledge graphs, semantic data or enterprise search.
• Experience with Claude and the Anthropic platform.
• Fluency in a second European language.