Forward Deployed Engineer - AI

About the Role

Enterprises are adopting AI faster than they can govern it, and they're looking for a partner who can do two things exceptionally well:

• Speak credibly about AI trust, governance and security.
• Build real AI solutions that solve business problems.

This isn't a traditional pre-sales role or a back-office delivery position. It's a highly autonomous customer-facing engineering role inspired by the engagement models used by leading AI companies—owning problems from discovery workshops through to production.

What You'll Do

• Advise on AI Trust & Governance
• Lead AI governance and discovery workshops
• Help customers understand and govern their AI landscape (agents, copilots, models and shadow AI)
• Explain AI governance, security posture and resilience to both technical and executive audiences
• Help establish: AI inventories, Approval workflows, Risk classifications, Audit evidence, Practical AI operating models
• Scope & Shape AI Projects
• Work directly with business stakeholders to understand the real business problem behind AI initiatives.
• Identify high-value AI use cases.
• Define success criteria.
• Translate ambiguous requirements into deliverable technical scopes.
• Produce: Architecture outlines, Data & integration requirements, Delivery phases, Effort estimates, Risk assessments, Write Statements of Work (SoWs) customers can sign and engineering teams can deliver.
• Build & Deliver
• Develop both prototypes and production-ready AI solutions including: AI agents, RAG pipelines, LLM integrations: Azure OpenAI, AWS Bedrock, Google Vertex AI, Anthropic, MCP-based tool integrations
• Governance and security controls
• Own Customer Delivery
• Remain the trusted technical advisor throughout the engagement by: Running enablement sessions, Supporting customer adoption, Troubleshooting production issues, Identifying opportunities to expand engagements where genuine customer value exists.

We're Looking For

• Must-Haves:
• 5+ years in Software Engineering, Solutions Architecture or Technical Consulting.
• 2+ years building modern AI/LLM solutions in production (not just experimentation).
• Hands-on experience with: Azure OpenAIAWS BedrockGoogle Vertex AILangChainSemantic Kernel
• Experience building: RAG solutions, Agentic workflows, Tool/function calling
• Strong programming skills in: Python, C#, TypeScript
• Experience with Azure, AWS or GCP, including identity, networking and data services.
• Proven ability to scope technical projects from ambiguous business requirements.
• Excellent communication skills—from board-level conversations through to deep technical discussions.
• Comfortable working autonomously in fast-moving client environments.
• Willingness to travel (~40%).
• Strong Pluses:
• AI Security: Prompt injection, Data leakage, Agent permissions, AI-SPM / DSPM
• Experience with: Model Context Protocol (MCP), Agent runtimes, Pinecone, Milvus
• Experience with Enterprise data governance, backup, resilience or Microsoft 365 ecosystems.
• Experience delivering into regulated industries: Public Sector, Defence, Financial Services, Healthcare
• Experience in air-gapped or sovereign cloud environments.
• Previous Forward Deployed Engineering, embedded consulting or customer-facing engineering experience.