Remote United Kingdom, London, England, United Kingdom; Munich, Germany
Work mode
remote
Type
full-time
Department
Technology
Last seen
22h ago
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.
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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:
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Whiteboarding AI trust and governance concepts with CISOs and executives.
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Translating business challenges into scoped AI delivery projects.
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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
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Lead AI governance and discovery workshops.
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Help customers understand and govern their AI landscape (agents, copilots, models and shadow AI).
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Explain AI governance, security posture and resilience to both technical and executive audiences.
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Guide organisations through:
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EU AI Act
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NIS2
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ISO/IEC 42001
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Help establish:
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AI inventories
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Approval workflows
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Risk classifications
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Audit evidence
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Practical AI operating models.
Scope & Shape AI Projects
Work directly with business stakeholders to understand the real business problem behind AI initiatives.
You’ll:
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Identify high-value AI use cases.
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Define success criteria.
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Translate ambiguous requirements into deliverable technical scopes.
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Produce:
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Architecture outlines
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Data & integration requirements
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Delivery phases
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Effort estimates
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Risk assessments
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Write Statements of Work (SoWs) customers can sign and engineering teams can deliver.
Build & Deliver
Develop both prototypes and production-ready AI solutions including:
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AI agents
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RAG pipelines
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LLM integrations:
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Azure OpenAI
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AWS Bedrock
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Google Vertex AI
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Anthropic
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MCP-based tool integrations
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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:
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Running enablement sessions.
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Supporting customer adoption.
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Troubleshooting production issues.
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Identifying opportunities to expand engagements where genuine customer value exists.
What We’re Looking For
Must-Haves
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5+ years in Software Engineering, Solutions Architecture or Technical Consulting.
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2+ years building modern AI/LLM solutions in production (not just experimentation).
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Hands-on experience with:
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Azure OpenAI
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AWS Bedrock
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Google Vertex AI
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LangChain
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Semantic Kernel
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Experience building:
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RAG solutions
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Agentic workflows
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Tool/function calling
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Strong programming skills in:
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Python
•
C#
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TypeScript
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Experience with Azure, AWS or GCP, including identity, networking and data services.
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Proven ability to scope technical projects from ambiguous business requirements.
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Excellent communication skills—from board-level conversations through to deep technical discussions.
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Comfortable working autonomously in fast-moving client environments.
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Willingness to travel (~40%).
Strong Pluses
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AI Governance & Compliance:
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EU AI Act
•
NIS2
•
ISO/IEC 42001
•
NIST AI RMF
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Gartner AI TRiSM
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AI Security:
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Prompt injection
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Data leakage
•
Agent permissions
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AI-SPM / DSPM
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Experience with:
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Model Context Protocol (MCP)
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Agent runtimes
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Pinecone
•
Milvus
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Weaviate
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Chroma
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Enterprise data governance, backup, resilience or Microsoft 365 ecosystems.
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Experience delivering into regulated industries:
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Public Sector
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Defence
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Financial Services
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Healthcare
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Experience in air-gapped or sovereign cloud environments.
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Previous Forward Deployed Engineering, embedded consulting or customer-facing engineering experience.
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