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. As a Forward Deployed Engineer (AI), you'll be the technical face of AvePoint inside enterprise customers.

You'll be equally comfortable: Whiteboarding AI trust and governance concepts with CISOs and executives. Translating business challenges into scoped AI delivery projects. Building the first working prototype yourself.

You'll embed with customers, own engagements end-to-end, and deliver tangible outcomes. 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.

Guide organisations through: EU AI Act NIS2 ISO/IEC 42001 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. You'll: Identify high-value AI use cases.

Define success criteria.

Requirements

into deliverable technical scopes.

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

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 Governance & Compliance: EU AI Act NIS2 ISO/IEC 42001 NIST AI RMF Gartner AI TRiSM AI Security: Prompt injection Data leakage Agent permissions AI-SPM / DSPM Experience with: Model Context Protocol (MCP) 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 Experience in air-gapped or sovereign cloud environments. Previous Forward Deployed Engineering, embedded consulting or customer-facing engineering experience.

What 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 OpenAI AWS Bedrock Google Vertex AI LangChain Semantic 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.