About Adelphi: Adelphi builds AI/ML-enabled secure data access and sharing technology for the U.S. intelligence and defense communities, using its Connector software product to enable federated data discovery that cuts intelligence-sharing time from months to minutes. The company's mission is to eliminate data silos, build trust in automation without compromising security, and improve information flow across mission-critical environments. Adelphi closed a $7M Seed round in August 2025 and has Customers across the Intelligence Community and the Department of War.

About the Role: The Forward Deployed Senior Machine Learning Engineer position requires a mix of software development, LLM Ops, and secdevops practices, resulting in an exciting, fast-paced engineering role. This role requires the ability to provide solutions for the full LLM stack, from the OS, storage, and network up to the API and transport layer. Experience in the defense or intelligence fields is required. You will own end-to-end delivery of agentic, full-stack systems built on top of frontier models, from first prototype to stable production, embedded alongside our defense and intelligence customers.

Location: This role is based in the DC/Metro area; remote candidates will be considered with 25% travel expected.

Clearance Requirement: An active U.S. Government clearance is strongly preferred, but we are open to clearance eligible candidates.

Is this you?

We are an AI-native engineering team. We expect every engineer to leverage LLMs and AI tooling as a core part of how they design, build, ship, and operate agentic systems that turn frontier-model capability into mission outcomes.

• You use AI coding tools (Claude Code, Cursor, Copilot) daily and instinctively.

• You prompt-engineer through complex architecture and debug sessions, leverage LLMs across the full development lifecycle, maintain a clear-eyed view of AI limitations in high-security contexts, and stay current with emerging models and tooling.

• Hands-on with modern agent frameworks and SDKs (LangGraph, OpenAI Agents SDK, Claude Agent SDK, AutoGen, or similar) and agent evaluation / observability tooling.

• Familiarity with MCP or similar LLM integration frameworks.

• You have a clear-eyed view of AI limitations. You know when to trust AI-generated output and when to verify.

Expectations:

• Own end-to-end delivery of agentic, full-stack systems from first prototype to stable production, embedded alongside defense and intelligence customers.

• Build and deploy ML services leveraging LLMs, embeddings, RAG, and agent orchestration into production environments, including classified and air-gapped ones.

• Work directly with customers to scope problems, sequence delivery, and ship novel AI applications under real-world constraints.

• Codify repeatable patterns into reusable tools and building blocks that help the team ship faster.

Bonus Points:

• Proficiency in infrastructure management (Docker, Kubernetes, AWS).

• Expertise in encryption, authentication, Linux systems administration, DevOps, or SRE.

• Production experience launching agentic services and forward-deployed AI applications that drive operational value at the customer site.

• Experience as a forward-deployed engineer or tech-led delivery role, embedded with mission customers, scoping problems, sequencing delivery, and shipping novel agentic applications under tight constraints

• Experience with federated or privacy-preserving data architectures (such as differential privacy and secure enclaves).

Benefits:

• Healthcare coverage: 100% employee premium and 50% dependents premium coverage of a platinum-level plan.

• 401K with 2% company match.

• $500 monthly Physical and Mental Health reimbursement program.

• Unlimited time-off policy.

• Competitive salary and equity compensation.

• Opportunity to work on impactful projects in the national security sector.

• Career growth and leadership opportunities in a dynamic, innovative environment.