Forward Deployed Engineer - AI

• 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.
• AI inventories
• Approval workflows
• Risk classifications
• Audit evidence
• Practical AI operating models.

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
• Architecture outlines
• Data & integration requirements
• Delivery phases
• Effort estimates
• Risk assessments
• Write Statements of Work (SoWs) customers can sign and engineering teams can deliver.

Develop both prototypes and production-ready AI solutions including:

• AI agents
• RAG pipelines
• LLM integrations: Azure OpenAI AWS Bedrock Google Vertex AI Anthropic
• Azure OpenAI
• AWS Bedrock

• Anthropic
• MCP-based tool integrations
• Governance and security controls

You'll also build custom tooling for regulated, cloud-restricted or air-gapped environments where SaaS solutions aren't suitable.

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.

• 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 OpenAI AWS Bedrock Google Vertex AI LangChain Semantic Kernel
• Azure OpenAI
• AWS Bedrock

• LangChain
• Semantic Kernel
• Experience building: RAG solutions Agentic workflows Tool/function calling
• RAG solutions
• Agentic workflows
• Tool/function calling
• Strong programming skills in: Python C# TypeScript
• 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%).

• AI Security: Prompt injection Data leakage Agent permissions AI-SPM / DSPM
• Prompt injection
• Data leakage
• Agent permissions

• Experience with: Model Context Protocol (MCP) Agent runtimes Pinecone Milvus Weaviate Chroma

• Agent runtimes
• Pinecone
• Milvus
• Weaviate
• Chroma
• Enterprise data governance, backup, resilience or Microsoft 365 ecosystems.
• Experience delivering into regulated industries: Public Sector Defence Financial Services Healthcare
• 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.

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Any personal data you share with us during the application process will be processed strictly in compliance with applicable data protection laws and our Privacy Notice .