Forward Deployed Engineer - AI

About AvePoint

AvePoint is the global leader in data protection, unifying data security, governance, and resilience to provide a trusted foundation for AI. More than 28,000 customers rely on the AvePoint Confidence Platform to secure, govern, and rapidly recover data across Microsoft, Google, Salesforce, and other cloud environments. With a single platform for lifecycle control, multicloud governance, and rapid recovery paired with clear ownership across the business, we prevent overexposure and sprawl, modernize legacy and fragmented data, and minimize data loss and interruption. Our global partner ecosystem includes approximately 6,000 MSPs, VARs, and SIs, and our solutions are available in over 100 cloud marketplaces. To learn more, visit www.avepoint.com.

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.

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 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 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.

The Salary Range for this role is $180,000 - $230,000. At AvePoint, we strive to offer competitive, fair, and equitable total rewards. The listed salary range represents a good faith estimate, with final offers based on location, experience, skills, and qualifications. The listed range reflects base salary only; our total rewards include base salary, comprehensive benefits (medical, dental, vision, 401(k) with match, unlimited PTO), and depending on the role, bonuses, commissions, or equity (RSUs). We welcome compensation discussions—apply even if your expectations fall outside the range.

Any personal data you share with us during the application process will be processed strictly in compliance with applicable data protection laws and our Privacy Notice.

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Any personal data you share with us during the application process will be processed strictly in compliance with applicable data protection laws and our Privacy Notice.