Forward Deployed AI Engineer

Role Description

In this role you will join a team building the backbone of modern defense software delivery — helping ensure warfighters can deploy the latest capabilities rapidly, securely, and reliably.

• Embed with strategic customers as a technical partner, working from problem discovery to solution implementation and customer adoption.
• Architect, build, deploy, and operate agentic Generative AI systems: APIs, data processing ETL pipelines, integration layers, Retrieval Augmented Generation, and context engineering.
• Work in cloud, on-prem, and edge/air-gapped environments to ensure software can run where the mission demands.
• Prototype and deploy systems leveraging the core products and design patterns of the Unicorn Delivery Service (UDS); bring back insights from the field for continuous product improvement.
• Scope, sequence, and lead delivery of solutions: define living roadmaps, set priorities, trade off speed vs quality vs scope, work across internal teams and customer stakeholders to drive clarity and remove blockers early.
• Codify reusable patterns for mission environments: build tools, internal frameworks, playbooks so future deployments are faster, safer, and repeatable.
• Act as the technical face to customer leadership: communicate effectively with both technical and non-technical stakeholders, build trust, manage expectations, and ensure successful scale and mission adoption. This is a customer-facing role.
• Ability and interest to travel up as needed to client sites, but flexible based on personal preferences.

Qualifications

• 3+ years of engineering or technical deployment experience (backend or full-stack), ideally in customer-facing or government environments (DoD, intelligence, public sector) or analogous high-assurance contexts.
• Strong backend engineering skills: production-grade code in Python or TypeScript; deep familiarity with designing services, APIs, data pipelines, integrations, and backend frameworks.
• Familiarity with LLMs or generative AI systems — be able to explain the fundamentals of Context Engineering and understand how model behavior connects to product/mission experience, and how AI capabilities integrate into larger system architectures.
• Strong ability to work in ambiguity: define scope, sequence work, make trade-offs between speed, quality, and scope; remove blockers; deliver under pressure in dynamic mission-driven settings.
• Excellent communication skills: able to translate complex technical details into clear messaging for non-technical stakeholders; work cross-functionally; build relationships with customers and internal teams.
• Mission-oriented mindset. Have an understanding that our work is supporting the defense and freedom of the nation.

Requirements

• Experience with deploying applications on Kubernetes inside of air-gapped or secure environments.
• Experience with Information Retrieval fundamentals including knowledge of keyword and vector based search, document parsing and chunking, document reranking, and SQL/NoSQL search engines.
• Experience with developing, executing, and maintaining LLM evaluations.
• Experience with open source LLM or SLM models (Llama3, Mixtral, Gemma, Phi) including inference frameworks, structured output, fine-tuning, and model architecture reconfiguration.

Benefits

• Health:
  • Medical/Dental/Vision
  • Premiums are 100% Company Paid
  • Health Reimbursement Account
  • Life Insurance
  • Disability Insurance
• Financial:
  • 401k Retirement Plan
  • Company Stock Options
  • Home Office Budget
• Leave:
  • Flexible Time Off (FTO) plus all Federal Holidays, one week for Thanksgiving, and two weeks for Christmas and New Year’s
  • Paid Parental Leave
• Learning:
  • Reimbursement for approved trainings/subscriptions
  • Conferences (travel, lodging, and fees)