Lead Engineer

This is a U. S. based position. All of the programs we support require U. S. citizenship to be eligible for employment. All work must be conducted within the continental U. S. Who we are: Raft ( com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U. S.

military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans. Our flagship AI platform, [R]AIMS (Raft AI Mission System), enables operators and engineers to rapidly build, deploy, and govern AI-powered mission workflows across highly dynamic operational environments. We are looking for an experienced Lead AI/ML Software Engineer to help shape the next phase of [R]AIMS: a technical builder-leader with deep experience designing and scaling complex production systems, someone who can make hard architecture decisions, simplify complexity, lead major engineering efforts, and raise the technical bar across the platform. About the role: As Lead Engineer for [R]AIMS, you will serve as a senior technical leader responsible for evolving the architecture, execution, and engineering rigor of Raft’s AI Mission System. You will be hands-on in the codebase, leading by doing, while also setting technical direction and raising the quality of engineering across the team. You will partner closely with platform leadership, product, and delivery teams to drive architectural decisions, lead major technical epics from conception through delivery, and establish the engineering patterns that the platform will grow on. You will operate at the intersection of distributed systems, AI/ML platform engineering, Kubernetes-native infrastructure, and data-intensive application development, balancing rapid mission delivery with long-term platform integrity. This role requires someone equally comfortable writing production systems with complex multi-vendor integrations, debugging difficult distributed systems issues, leading design reviews, and making pragmatic tradeoff decisions under ambiguity.