Chief Engineer

Quantum Sky•Reston, VA

2d•$225,000 - $265,000

About The Position

Project 137 is Quantum Sky’s IP and solution engine, organized around Quantum, Digital Platforms, Decision Advantage, and Cyber practices. The Chief Engineer turns solutions devised by those practices into software that runs and is accountable for how it is built. The role leads development of modern, cloud-native microservice applications for U.S. government customers, including DoD/DoW, the Intelligence Community, and federal civilian agencies. Increasingly, these applications will include agents and agentic workflows that perform real work alongside users. The Chief Engineer sets the engineering standard for Project 137 and its programs, delivering software that is secure, scalable, compliant, and accessible by design. The role leads both engineering and modernization of the development lifecycle through an agentic SDLC, using AI agents to assist with design, coding, testing, security, review, and delivery while meeting federal delivery and accreditation requirements. It also demonstrates modern software delivery within federal boundaries and supports customer missions across government and classified cloud regions, on-premises enclaves, hybrid estates, and disconnected or bandwidth-constrained edge environments. This is a hands-on builder-leader position: the Chief Engineer remains technically engaged while leading engineering teams, setting architecture and quality standards, strengthening common engineering foundations across the practices, developing talent, and helping teams deliver credible customer demonstrations. The role reports to a specific position not stated in the posting.

Requirements

15+ years of software engineering and engineering leadership experience, including 7+ years building and delivering software for the federal government (DoD/DoW, Intelligence Community, or federal civilian).
Deep, hands-on experience designing and delivering cloud-native microservice applications using containers and Kubernetes, service mesh, event streaming, API management, and associated data patterns in AWS, Azure, or Google government environments.
Experience building systems that scaled under real load and the ability to explain the challenges encountered.
A record of building and operating DevSecOps pipelines in federal environments, including CI/CD, infrastructure as code, automated testing, static and dynamic security testing, software composition analysis, SBOMs, software supply-chain security, and software factory or continuous ATO practices.
Evidence of shipping federal software that passed security assessment, performed in operation, and remained patched.
Working approach to open-source governance, including license, provenance, and vulnerability management across a real dependency tree.
Hands-on experience building LLM-based and agentic applications, including orchestration frameworks, retrieval, tool calling, Model Context Protocol, evaluation, and guardrails.
Experience using AI coding agents to accelerate the software lifecycle, with the ability to explain where agents create leverage and risk to an authorizing official.
Track record leading multiple engineering teams through delivery against federal contracts, schedules, and accreditation requirements, and developing engineers.
Working fluency in NIST 800-53, RMF, FedRAMP, DoD Cloud Computing Security Requirements Guide impact levels, NIST Secure Software Development Framework (SP 800-218), DoD Zero Trust Reference Architecture, and Section 508/WCAG accessibility, including how these standards affect software design and delivery.
Active SECRET clearance or higher; Top Secret/SCI preferred.

Nice To Haves

Experience building for DoD/DoW or Intelligence Community mission customers, including in classified environments.
Experience delivering software to disconnected, intermittent, and limited-bandwidth (DDIL) and tactical edge environments.
Prior leadership of an engineering practice, software factory, or product line with accountability for reuse, cost, and growth.
Recognized point of view on modern federal software delivery or agentic engineering, demonstrated through talks, published work, open-source contributions, or industry working groups.
Top Secret/SCI clearance preferred.

Responsibilities

Set target architecture for Project 137 applications, including containerized microservices, event-driven integration, API-first design, and agentic services.
Design systems for government and classified cloud regions, on-premises enclaves, hybrid environments, and disconnected or bandwidth-constrained edge deployments; balance cloud-native design with portability where needed.
Lead software engineers in taking solutions from concept to demonstrable, accredited, deployable capability.
Build production-ready agentic workflows, including orchestration, tool use, memory, guardrails, evaluation, observability, and human oversight where mission needs require it.
Own software quality and assurance, including secure design, continuous scanning, vulnerability remediation, vulnerability backlog management, load and resilience testing, and cost testing.
Ensure federal cybersecurity, compliance, and accessibility requirements—including NIST and FedRAMP controls, DoD impact levels, and Section 508—are built into development pipelines.
Govern open-source dependencies through approved components, license compliance, provenance, SBOMs, and assessment of project health; contribute to open source when beneficial to the mission and company reputation.
Establish and operate an agentic SDLC and DevSecOps pipeline incorporating AI-assisted design, coding, testing, code review, security scanning, CI/CD controls, provenance, and accreditation evidence.
Measure and demonstrate improvements in delivery velocity, quality, and cost.
Partner with leaders of the Quantum, Digital Platforms, Decision Advantage, and Cyber practices to establish reusable services, shared platforms, and common engineering patterns across the portfolio.
Recruit, develop, and retain engineers skilled in modern software and agentic AI who can work in cleared environments; set engineering standards and decide what to build, buy, or obtain through partners.
Lead teams in delivering compelling, functional, and credible demonstrations; coach demo teams on the story, script, and recovery from live failures, and lead technical demonstrations when appropriate.
Remain technically engaged by reading and writing code, making explicit architecture trade-offs, and communicating clearly with business leaders, program and capture managers, program executives, authorizing officials, and developers.
Surface release risks early and plainly, and guide customers through modernization while identifying appropriate uses for agentic AI.
Lead multiple engineering teams delivering against federal contracts, schedules, and accreditation requirements, while growing engineers on those teams.