Forward Deployed AI Engineer (FedD149B/ FedD110)

Role Description:

Defense Unicorns is seeking a Senior Forward Deployed AI Engineer to embed with defense and national security customers as a technical partner, owning solutions from problem discovery through production deployment. The work centers on backend engineering, data pipelines, and retrieval systems that power agentic and generative AI capabilities on top of Defense Unicorns' core platform (Unified Defense Stack). You'll deploy and operate these systems across cloud, on-prem, and air-gapped environments, then carry field insights back to product and engineering to improve the platform. This is a customer-facing, delivery-focused role, not an ML research position.

Responsibilities:

• Embed with strategic customers as a technical partner, owning the arc from problem discovery through solution delivery and customer adoption.
• Architect, build, and deploy backend systems that power generative AI capabilities: APIs, data processing pipelines, integration layers, Retrieval Augmented Generation (RAG), and context engineering patterns.
• Deploy and operate systems in cloud, on-prem, and air-gapped environments using Defense Unicorns' core platform and delivery patterns.
• Scope and sequence delivery: define roadmaps, set priorities, make speed/quality/scope tradeoffs, and remove blockers across internal teams and customer stakeholders.
• Codify reusable patterns for mission environments: tooling, internal frameworks, and playbooks that make future deployments faster and more repeatable.
• Serve as the technical face to customer leadership: translate complex technical work for non-technical stakeholders, build trust, and drive adoption.
• Carry field insights back to product and engineering teams to improve the platform based on what's actually breaking or missing in production.
• Prototype and validate new capabilities using core products and design patterns, feeding lessons learned back into the product.

Travel Expectations/Requirements: Up to 25%, flexible based on engagement needs

The listed responsibilities are not exhaustive and additional responsibilities may be assigned based on the evolving needs of the organization. We are seeking a dynamic individual who is able to adapt and take on new responsibilities as they arise.

Required Experience and Qualifications:

• 4+ years of backend or full-stack engineering experience, with production-grade work in Python.
• Experience designing and operating data pipelines, APIs, and integration layers in production.
• Hands-on experience with information retrieval systems: keyword search, vector search, document parsing and chunking, reranking, or search engine internals (Elasticsearch, OpenSearch, or similar).
• Working knowledge of RAG patterns or applied generative AI: connecting LLMs to real data sources in a production context.
• Experience deploying or operating software in government, defense, or similarly regulated environments (or equivalent high-assurance contexts).
• Strong communication skills: able to translate technical work into clear language for non-technical stakeholders and build trust with customers.
• Comfort with ambiguity and shifting priorities. You take initiative, define your own work when direction is unclear, and deliver under pressure.
• Eligibility to obtain a U.S. security clearance.

Preferred Experience and Qualifications:

• Experience deploying applications on Kubernetes in air-gapped or classified environments.
• Familiarity with open-source LLMs/SLMs (Llama, Mixtral, Gemma, Phi), including inference frameworks, structured output, or fine-tuning.
• Experience developing and maintaining LLM evaluation frameworks.
• Background in document processing pipelines: parsing, chunking, embedding, and indexing at scale.
• Active security clearance (Secret or above; TS/SCI preferred).
• Prior customer-facing or forward-deployed engineering experience.