Forward Deployed Engineer - AI

JobsCloseBy Editorial Insights

AvePoint is hiring a Forward Deployed Engineer AI in London to be the technical face of the company inside enterprise customers, owning engagements from discovery to production and blending credible AI governance with real, production ready solutions. The role demands 5+ years in software engineering or technical consulting, 2+ years building production AI and LLM solutions, and hands on work with Azure OpenAI, AWS Bedrock, Google Vertex AI, LangChain and Semantic Kernel; you’ll scope ambiguous business problems into SoWs, design data and integration needs, build prototypes, RAG pipelines and governance controls, and travel roughly 40%. Strong communication across board and technical teams is essential, as is autonomous execution in fast moving client environments. To apply, tailor your CV to highlight production AI deployments, governance work, prototypes or tooling you’ve built, and readiness to engage executives and travel; add links to relevant projects and be ready to discuss how you would approach AI trust and governance in regulated contexts.

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.
• 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

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.

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.
• 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 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.

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