Lead Engineer

Description

The role is based in the U.S. Every program the company supports requires U.S. citizenship for employment, and all work must take place within the continental U.S.

The company is a non-traditional defense technology firm that builds AI, machine learning and data solutions for U.S. military and government agencies. It is headquartered in McLean, VA, and works in autonomous data fusion and agentic AI, with a focus on distributed data systems, large-scale platforms and complex application development.

Its flagship AI platform helps operators and engineers build, deploy and govern AI-powered mission workflows in fast-changing operational settings.

The team is looking for a senior technical leader to help guide the platform's next phase. This person will make hard architecture calls, simplify complicated systems, lead large engineering efforts and raise the technical standard across the team.

You will work hands-on in the codebase while setting technical direction and improving engineering quality across the team. You will work with platform leadership, product and delivery teams on architecture, major technical efforts and the engineering patterns the platform will be built on. The work sits where distributed systems, AI/ML platform engineering, Kubernetes-native infrastructure and data-intensive applications meet, and it balances fast mission delivery with long-term platform health.

The role suits someone who can write production systems with complex multi-vendor integrations, debug hard distributed systems problems, lead design reviews and make practical tradeoffs when the picture is unclear.

Responsibilities

• Make architecture decisions for the platform by weighing performance, scalability, security and maintainability, and get engineering and product stakeholders aligned on them.
• Lead major technical efforts from initial concept through delivery. Break unclear problems into concrete plans and keep cross-functional teams moving with clear direction.
• Simplify the distributed architecture as the platform grows, cutting unnecessary complexity and improving operational reliability without losing capability.
• Improve platform performance on both edge and cloud deployments by finding and fixing bottlenecks in data-heavy, latency-sensitive environments.
• Build solid engineering foundations and reusable technical patterns that make developers more productive and raise code quality.
• Mentor engineers at every level through design reviews, detailed code feedback and hands-on help that raises technical execution across the platform.
• Work with AI/ML engineers on model integration, inference optimization and deploying agentic workflows in the platform.
• Work directly with customers and program stakeholders in demanding Department of Defense environments, presenting the company's technical capabilities clearly and credibly.

Requirements

• At least 6 years of hands-on experience building and shipping production software across the full stack, including frontend, backend, infrastructure and ML.
• Strong software engineering fundamentals and a record of designing, building and evolving complex systems that run reliably at scale.
• Excellent technical communication. You can lead through influence across engineering, product and leadership without formal authority.
• Proven experience designing and evolving distributed systems, covering service decomposition, inter-service communication, fault tolerance and observability.
• Solid hands-on experience with Kubernetes and cloud-native platform architecture in production.
• Experience building data-intensive or AI-enabled production systems used by real operators under real performance limits.
• Proven technical leadership of large, cross-functional engineering initiatives, with clear ownership of outcomes.
• Strong system design and architecture decision-making, with a history of making sound calls on incomplete information.
• Some experience or exposure to training, fine-tuning or deploying machine learning models in production.
• Ability to obtain Security+ certification within 90 days of starting.
• U.S. citizenship is required. You must be able 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.
• Highly preferred: experience with streaming and event-driven architectures, particularly Kafka, Kafka Streams or Apache Flink.
• Highly preferred: experience with platform engineering and internal developer tooling, such as golden-path frameworks, shared libraries and developer experience work.
• Highly preferred: experience with real-time inference or operational AI systems in latency-sensitive settings.
• Highly preferred: experience building secure, compliant systems for regulated or mission-critical environments, including familiarity with IL4, IL5 or IL6 requirements or RMF processes.
• Highly preferred: prior work in defense, national security or classified program environments.
• Highly preferred: an active clearance.

Conditions

Remote work within the U.S. Candidates located near one of the company's hubs (McLean, VA; Colorado Springs, CO; Tacoma, WA; Oahu, HI; Tampa, FL; or Boston, MA) are preferred.

Travel of up to 25% is required.

No clearance is required to start. You must be eligible for and willing to obtain a Top Secret/SCI clearance. An active clearance is preferred.

The company is an equal opportunity employer and considers all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status or disability status.

Benefits

• Competitive salary.
• Fully covered healthcare, dental and vision coverage.
• 401(k) with company match.
• Flexible PTO plus 11 paid holidays.
• Education and training benefits.
• Generous referral bonuses.
• Additional benefits beyond those listed.