Forward Deployed Engineer - AI

Socket.dev

Chicago (IL)

On-site

USD 140,000 - 210,000

Full time

14 days+

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Job summary

AvePoint is seeking a Forward Deployed Engineer (AI) to be the technical face with enterprise customers, shaping AI governance, delivering prototypes and production AI solutions, and owning end-to-end engagements.

You will translate business challenges into scoped AI delivery projects, lead workshops, and build tangible AI outcomes across cloud environments with autonomy and frequent travel.

Qualifications

5+ years in Software Engineering, Solutions Architecture or Technical Consulting.
2+ years building modern AI/LLM solutions in production.
Hands-on experience with Azure OpenAI, AWS Bedrock, Google Vertex AI.
LangChain and Semantic Kernel experience; RAG solutions and agentic workflows.
Strong programming skills: Python, C#, TypeScript.
Experience with cloud providers (Azure, AWS or GCP).
Ability to scope technical projects from ambiguous requirements.
Excellent communication from board level to technical teams.
Willingness to travel (~40%).

Responsibilities

Advise on AI Trust & Governance for enterprise clients.
Scope and shape AI projects with stakeholders; produce architecture outlines and SOWs.
Deliver prototypes and production AI solutions including agents and RAG pipelines.
Own customer delivery and run enablement sessions; support adoption and troubleshooting.

Skills

Software Engineering

Solutions Architecture

Technical Consulting

AI/LLM production

Python

TypeScript

Board-level communication

Autonomy

Tools

Azure OpenAI

AWS Bedrock

Google Vertex AI

LangChain

Semantic Kernel

RAG

Agentic workflows

Tool/function calling

Pinecone

Milvus

Weaviate

Chroma

Job description

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 expand 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
  - Defense
  - Financial Services
  - Healthcare
- Experience in air-gapped or sovereign cloud environments.
- Previous Forward Deployed Engineering, embedded consulting or customer-facing engineering experience.
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.