Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

About the Role

The Forward Deployed Engineer (AI) partners with clients to address the growing need for AI trust, governance, and security, while also building AI solutions. This role involves embedding with clients to understand business problems, scope AI projects, and develop prototypes and production components. You will act as the technical face of the company, owning engagements from initial workshops to production.

Responsibilities

Advise on AI trust and governance.
Lead workshops to help clients understand and control their AI landscape, including agents, copilots, models, and data.
Explain AI governance, security posture, and resilience concepts to both technical teams and executives.
Guide clients through obligations such as the EU AI Act, NIS2, and ISO 42001.
Help clients establish practical operating models for AI, including inventories, approval workflows, risk classification, and audit evidence.
Scope and shape AI build projects by understanding business needs and identifying high-value use cases.
Define success criteria and translate ambiguous requirements into concrete technical scopes.
Produce architecture outlines, data and integration requirements, delivery phases, and effort/risk assessments.
Write statements of work for engineering teams and clients.
Develop prototypes and production components for client AI solutions, including agent workflows, RAG pipelines, and LLM integrations.
Deliver custom adapters and local tooling for regulated, cloud-restricted, or air-gapped environments.
Act as the trusted technical advisor from first workshop through go-live.
Run enablement sessions and support client adoption.
Troubleshoot in production and expand engagements where value is identified.

Requirements

5+ years in software engineering, solutions architecture, or technical consulting.
At least 2 years hands-on experience with modern AI/LLM systems in real projects.
Practical experience building with LLM APIs and frameworks (e.g., Azure OpenAI, Bedrock, Vertex, LangChain, Semantic Kernel).
Experience with patterns such as RAG, agentic workflows, and tool/function calling.
Hands-on machine learning experience spanning model development, evaluation, deployment, and operationalization, with a focus on enterprise AI solutions, predictive analytics, and scalable MLOps practices.
Strong programming skills in Python and/or C#/TypeScript.
Working fluency with at least one major cloud platform (Azure, AWS, or GCP), including identity, networking, and data services.
Demonstrated ability to scope technical projects from ambiguous business requirements.
Ability to run a requirements workshop, constructively challenge assumptions, and produce a credible plan with phases, estimates, and risks.
Excellent communication skills in front of senior stakeholders.
Willingness to travel to client sites.
Ability to operate with high autonomy in ambiguous, fast-moving engagements.
Working knowledge of AI governance and compliance frameworks (EU AI Act, NIS2, ISO/IEC 42001, NIST AI RMF, or Gartner's AI TRiSM model) is a strong plus.
Experience with AI security topics (prompt injection, data leakage, agent permissioning, model and data security posture) is a strong plus.
Familiarity with the Model Context Protocol (MCP), agent runtimes, or vector databases (e.g., Pinecone, Milvus, Weaviate, Chroma) is a strong plus.
Background in enterprise data governance, security, backup/resilience, or the Microsoft 365 / multi-cloud ecosystem is a strong plus.
Experience delivering into regulated industries (public sector, defense, financial services, healthcare) or air-gapped/sovereign environments is a strong plus.
Prior experience in a forward-deployed, embedded consulting, or customer-facing engineering role is a strong plus.
Additional languages relevant to the client base are a strong plus.

Skills

AI Trust
AI Governance
AI Security
LLM APIs
RAG
Agentic Workflows
Tool/Function Calling
Machine Learning
MLOps
Python
C#
TypeScript
Azure
AWS
GCP
Cloud Services
Communication
Technical Consulting
Solutions Architecture
Software Engineering
EU AI Act
NIS2
ISO 42001
NIST AI RMF
AI TRiSM
Prompt Injection
Data Leakage
Agent Permissioning
Model Security
Data Security
MCP
Vector Databases
Enterprise Data Governance
Enterprise Security
Backup and Resilience
Microsoft 365
Multi-cloud Ecosystem

Location

Client Sites

Work Type

Full-time
Embedded

Experience Level

5+ years software engineering/solutions architecture/technical consulting
2+ years hands-on AI/LLM systems

About the Company

AvePoint has two decades of enterprise data governance and resilience expertise.

Equal Opportunity

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.