Job Description Help for Job Description. Opens a new window. 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 () 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. What you'll do: 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 What we are looking for: 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 Highly preferred: Experience building AI/ML infrastructure or agentic systems, including orchestration frameworks, tool-use patterns, and LLM integration in production Experience with streaming and event-driven architectures, particularly Kafka, Kafka Streams, or Apache Flink Experience with platform engineering and internal developer tooling, including golden-path frameworks, shared libraries, and developer experience improvements Experience with real-time inference or operational AI systems in latency-sensitive environments Experience building secure, compliant systems for regulated or mission-critical environments, including familiarity with

IL4/IL5/IL6

requirements or RMF processes Prior work in defense, national security, or classified program environments Active clearance preferred What Success Looks Like [R]AIMS has a coherent, well-documented architecture that engineers at all levels understand and can contribute to confidently Major platform initiatives ship on time with high engineering quality, low rework rates, and clear technical rationale behind key decisions The engineering team is measurably stronger because of your presence: better design reviews, sharper code, cleaner systems Customers trust Raft technically. When you're in the room, they leave the conversation with confidence in what we're building and how we're building it Platform complexity is decreasing relative to capability, not increasing

Clearance Requirements:

No clearance required to start Must be eligible for and willing to obtain a Top Secret/SCI clearance; active clearance preferred

Salary Range:

$180,000.00 - $230,000.00

Work Type:

Remote within the U.S.; preference for candidates located near a Raft hub (McLean, VA; Colorado Springs, CO; Tacoma, WA; Oahu, HI, Tampa, FL; Boston, MA) Up to 25% travel What we will offer you: Highly competitive salary Fully covered healthcare, dental, and vision coverage 401(k) and company match Take as you need

PTO + 11

paid holidays Educatio... Visit the Employer site for more details