Forward Deployed Engineer - AI

AvePoint•Chicago, IL

15h•Hybrid

About The Position

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, and 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, and 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.

Requirements

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 and Agentic workflows.
Experience with 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%).

Nice To Haves

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.

Responsibilities

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.
Help establish AI inventories, Approval workflows, Risk classifications, Audit evidence, and Practical AI operating models.
Scope & Shape AI Projects
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.
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, and Governance and security controls.
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, and identifying opportunities to expand engagements where genuine customer value exists.