> Markdown version of [/jobs/ext/4008330-forward-deployed-engineer-ai](https://www.wearedevelopers.com/jobs/ext/4008330-forward-deployed-engineer-ai). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Forward Deployed Engineer - AI

- **Company:** AvePoint
- **Location:** New York, NY, United States
- **Experience:** Experienced
- **Salary:** $180,000.0 - $230,000.0
- **Contract:** Permanent contract
- **Skills:** Microsoft Windows, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Backup Devices, C Sharp (Programming Language), Software as a Service, Cloud Computing, Cyber Security, Computer Programming, Data as a Services, Data Governance, Data Integration, Information Leak Prevention, Data Recovery, Data Security, Python (Programming Language), Microsoft Software, OpenAI, Salesforce.Com, Software Engineering, TypeScript, Pinecone, Retrieval-Augmented Generation, Large Language Models, Google Vertex AI, Agentic-AI, Weaviate, Milvus, Invoking Functions, Model Context Protocol, Semantic Kernel, ChromaDB
- **Published:** October 29, 2026
- **Apply:** https://www.careerbuilder.com/job-details/forward-deployed-engineer-ai-new-york-ny--da2c7a12-e1e5-448d-a521-17901f4b3929

## About the Role

Artificial Intelligence (AI), Salesforce.com, Ecosystems, Cloud Computing, Microsoft Product Family, Information/Data Security (InfoSec), Artificial Intelligence (AI), Value-Added Resellers (VAR), Data Recovery, Problem Solving Skills, 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 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.

## 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.