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.
• 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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