About the Role
Defense Unicorns is veteran-founded and mission-driven, aiming to advance freedom and independence globally by transforming how the U.S. Department of War builds, buys, delivers, and sustains software. The company delivers secure, scalable software and AI solutions that function in cloud, on-prem, and tactical edge / air-gapped environments. In this role, you will join a team building the backbone of modern defense software delivery, ensuring warfighters can deploy the latest capabilities rapidly, securely, and reliably.
As a Forward Deployed AI Engineer at Defense Unicorns, you will directly contribute to accelerating warfighter capability. By working at the intersection of backend software engineering, secure delivery platforms, and mission-driven deployments, you’ll help deliver software updates in minutes instead of months — enabling operational advantage, agility, and freedom for the nation. You will not just build code — you’ll deploy impact where it matters most.
What You’ll Do
- 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.
What You’ll Bring
- 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.
Nice to Have
- 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.
What We Work On (Relevant Technologies)
- Kubernetes
- Cloud Environments (AWS/GCP and Azure)
- Infrastructure-as-code (like Terraform/Pulumi)
- Continuous Delivery and automation tooling
- GitOps
- Containers
- CNCF projects and open source products and packages
- Helm/Kustomize-Value Stream Mapping
- Building and improving security delivery
- Building Kubernetes and cloud native applications