Lead Engineer, Raft

• 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
• 6+ years of hands-on experience building and shipping production software systems across the full stack (frontend, backend, infrastructure, and ML)
• Deep software engineering fundamentals with demonstrated ability to design, build, and evolve complex systems that perform reliably at scale
• Exceptional technical communication skills; able to lead through influence across engineering, product, and leadership stakeholders without requiring direct authority
• Proven experience designing and evolving distributed systems, including service decomposition, inter-service communication patterns, fault tolerance, and observability
• Strong hands-on experience with Kubernetes and cloud-native platform architecture in production environments
• Experience building data-intensive or AI-enabled production systems with real operational users and real performance constraints
• Demonstrated technical leadership over large, cross-functional engineering initiatives with clear ownership and accountability for outcomes
• Strong system design and architecture decision-making ability, with a track record of making the right call under incomplete information
• Some experience or exposure to training, fine-tuning, or deploying machine learning models in production contexts
• Ability to obtain Security+ certification within the first 90 days of employment
• US citizenship required; ability to obtain and maintain a Top Secret/SCI clearance
• No clearance required to start
• Must be eligible for and willing to obtain a Top Secret/SCI clearance; active clearance preferred

Desirable

• 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
• Drive architectural decisions across the [R]AIMS platform, evaluating tradeoffs across performance, scalability, security, and maintainability and building alignment across engineering and product stakeholders
• Lead major technical epics from conception through delivery, decomposing ambiguous problems into executable plans and keeping cross-functional teams moving with clarity and momentum
• Simplify and rationalize distributed system architecture as the platform scales, reducing incidental complexity and improving operational reliability without sacrificing capability
• Optimize platform performance across both edge and cloud deployment targets, identifying and resolving bottlenecks in data-intensive, latency-sensitive operational environments
• Establish strong engineering foundations and reusable technical patterns that improve developer productivity and code quality across the team
• Mentor engineers at multiple levels, conducting design reviews, providing substantive code feedback, and actively elevating technical execution across the platform
• Partner with AI/ML engineers on model integration, inference optimization, and the operational deployment of agentic workflows within [R]AIMS
• Engage directly with customers and program stakeholders at operationally demanding environments across the Department of Defense, representing Raft’s technical capabilities with credibility and clarity