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Own end-to-end recruiting for technical and non-technical roles, including sourcing passive candidates, conducting introductory calls, partnering with hiring managers, managing ATS data and scheduling, communicating with candidates, closing offers, and supporting recruiting process, employer brand, and referral-program development.

Own architecture and technical direction for mission-critical Rust services, including an AI/API gateway, policy engine, Kubernetes controller, and ingestion worker. Write production Rust code while supporting Kubernetes, Helm, Argo CD, AWS EKS, Terraform, and Python tooling. Use AI coding tools daily, support secure government deployments, and contribute to on-call, observability, security engineering, and agentic AI services.

Own delivery planning for public-sector AI programs, including product requirements documents, roadmaps, backlogs, timelines, scope, and agile delivery cadence. Translate customer mission needs into actionable engineering work, define completion criteria, maintain delivery reporting and metrics, and establish repeatable intake and delivery processes. The role is forward deployed with engineering teams, customer-facing, and requires active Secret-level or higher U.S. government clearance.

The Senior ML Engineer will develop and deploy full-stack AI solutions, manage LLM integration, and collaborate closely with defense clients to enhance real-world applications in secure environments.

Build and deploy agentic, full-stack AI systems using LLMs, embeddings, RAG, and agent orchestration for defense and intelligence customers. Collaborate with customers, operate in classified/air-gapped environments, codify reusable patterns, and support end-to-end delivery from prototype to production.