Forward Deployed AI Engineer Lead

Job Family

Data Science Consulting

Travel Required

Up to 10%

Clearance Required

Ability to Obtain Public Trust

What You Will Do

As a Forward Deployed AI Engineer Lead, you will work directly with clients and multidisciplinary delivery teams to turn complex business and mission needs into practical, production-ready AI solutions. You will operate at the intersection of AI, software engineering, data, and client delivery, moving quickly from ambiguous problems to working prototypes, integrated solutions, and scalable implementation patterns.

This role combines hands-on engineering, client-facing technical leadership, innovation, and team development. You will lead complex forward deployed engagements while helping build the next generation of Forward Deployed Engineers through hands-on mentorship, technical coaching, and repeatable engineering and delivery best practices.

Forward Deployed Engineering & Solution Delivery

• Lead forward deployed engineering engagements, partnering directly with clients to understand complex workflows, identify high-value opportunities, and translate business and mission needs into working AI solutions.
• Rapidly design, prototype, test, and deploy generative AI and agentic AI applications within complex enterprise environments.
• Build advanced AI solutions using leading large language models, APIs, developer tooling, and enterprise AI platforms.
• Translate ambiguous and evolving requirements into practical technical designs, prototypes, and production-ready solutions.
• Design and implement agentic architectures incorporating Model Context Protocol (MCP), agent-to-agent (A2A) communication, retrieval-augmented generation (RAG), tool use, structured outputs, orchestration, context management, and human review where appropriate.
• Lead technical discovery sessions, architecture discussions, demonstrations, and hands-on solution working sessions with client stakeholders.
• Partner directly with users throughout implementation to gather feedback, diagnose challenges, refine solutions, and drive adoption.
• Identify innovative and practical ways to apply emerging AI capabilities to complex client challenges while balancing usability, performance, security, maintainability, and responsible AI.

Engineering & Integration

• Architect, build, and maintain integrations with internal and external systems using APIs, services, data pipelines, and modern application development practices.
• Design AI applications and agents that interact with enterprise data, tools, business systems, APIs, and other agents.
• Design and implement MCP-based integrations connecting AI applications and agents with enterprise tools, services, and data sources.
• Design and implement A2A and multi-agent patterns enabling specialized agents to coordinate and communicate as part of broader workflows.
• Design and implement RAG solutions, including enterprise knowledge retrieval, embeddings, vector search, grounding, and related retrieval patterns.
• Apply modern software engineering practices to move solutions from rapid prototype through testing, deployment, and operational support.
• Work with relational databases, vector stores, retrieval systems, APIs, and related data patterns to support application state, knowledge retrieval, traceability, and auditability.
• Implement testing, evaluation, logging, monitoring, and observability for AI-enabled applications and agentic workflows.
• Diagnose complex technical and integration issues across applications, models, agents, APIs, data, and infrastructure.
• Establish reusable technical patterns and accelerators that improve the quality and speed of future implementations.

Client & Technical Leadership

• Serve as a trusted senior technical advisor to clients on complex generative AI and agentic AI initiatives.
• Build relationships with technical, business, data, and leadership stakeholders, connecting client needs with practical technical solutions.
• Communicate complex technical concepts, solution options, risks, and trade-offs clearly to technical teams, business stakeholders, and senior client leaders.
• Facilitate technical discovery and working sessions that turn ambiguous client problems into actionable engineering decisions and solution approaches.
• Present prototypes, solution demonstrations, architecture decisions, and technical recommendations to client stakeholders.
• Ask effective questions, listen to client needs, and adapt technical approaches based on business, mission, user, and technology considerations.
• Challenge assumptions constructively and propose innovative approaches when conventional solutions do not adequately address the problem.
• Balance rapid experimentation and creative problem-solving with the engineering discipline required to deliver reliable, secure, maintainable, and scalable solutions.

FDE Capability Building & Mentorship

• Mentor and develop junior and mid-level engineers into effective Forward Deployed Engineers, building both their technical engineering skills and client-facing delivery capabilities.
• Coach team members on FDE best practices, including technical discovery, problem decomposition, requirements translation, rapid prototyping, solution design, client communication, demonstrations, implementation, troubleshooting, and knowledge transfer.
• Provide hands-on technical direction, architecture guidance, code review, pairing, and engineering mentorship.
• Develop and promote reusable FDE playbooks, engineering standards, solution patterns, accelerators, and implementation best practices.
• Coach team members on modern agentic AI engineering patterns, including MCP, A2A, RAG, tool use, orchestration, evaluation, and responsible AI practices.
• Help engineers become comfortable operating in ambiguous client environments and moving independently from problem identification through working solution.
• Create opportunities for junior team members to progressively