Lead Engineer
Tampa, FLAll locationsTampa, FLMcLean, VAColorado Springs, COTacoma, WAOahu, HIBoston, MA Remote
$180,000–$230,000 a yearJobFig found this opening at its original source and checks that it remains available.
About the role
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. 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.
What you'll bring
- 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
- ability to obtain and maintain a Top Secret/SCI clearance