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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Forward Deployed Engineer - AI - **Company:** AvePoint - **Location:** Chicago, IL, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Microsoft Windows, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Backup Devices, C Sharp (Programming Language), Software as a Service, Computer Programming, Data as a Services, Data Governance, Data Integration, Information Leak Prevention, Python (Programming Language), Software Engineering, TypeScript, Google Cloud, Large Language Models - **Published:** July 28, 2026 - **Apply:** https://www.dice.com/job-detail/96951d4b-2a97-4ee2-9777-480495bf348e ## About the Role 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 Google Cloud Platform, 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 Security: + Prompt injection + Data leakage + Agent permissions + AI-SPM / DSPM * Experience with: + Model Context Protocol (MCP) + Agent runtimes ## Description 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. * 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., + 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. ## Related Videos - [Azure AI Foundry for Developers: Open Tools, Scalable Agents, Real Impact](https://www.wearedevelopers.com/videos/1541-azure-ai-foundry-for-developers-open-tools-scalable-agents-real-impact) - [Hate organising your photos? 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