C++ Software Engineer with Security Clearance

Responsibilities
Design, implement, and maintain high-performance C++ applications and libraries across assigned products.
Develop new features and maintain legacy code in existing codebases.
Apply strong correctness, robustness, and performance discipline under technical direction from the project architect.
Work with multithreading, concurrent programming, and object lifecycle management in production systems.
Build and operate within our CI/CD pipeline: Git, GitLab, Docker, Linux, scripting, and Make-based builds.
Participate in code reviews as a contributor; incorporate feedback and raise quality through collaboration.
Use AI-assisted development tools effectively — including frontier LLMs, agentic coding workflows, and MCP-integrated tooling — as a routine part of delivering and reviewing software.
Collaborate with cross-functional engineers (Python, React, infrastructure) on integration points and API contracts.
Debug complex issues across distributed components and legacy subsystems.
Required qualifications
Deep understanding of C and C++ fundamentals — language semantics, memory model, and runtime behavior — not merely familiarity with the standard library.
Solid grounding in computing principles: algorithms, data structures, and systems thinking.
Multithreading and concurrent programming experience, including safe object lifecycle management.
Proven ability to analyze, navigate, and extend complex codebases — including legacy code.
Strong problem-solving and debugging skills on Linux server environments.
Proficiency with Git and willingness to adopt team workflows.
Hands-on experience with CI/CD tooling: GitLab, Docker, Linux shell scripting, and build automation (Make; CMake familiarity is a plus).
Automated testing experience; we use Google Test (gtest) for C++.
Strong communication and collaboration skills.
U.S. citizenship and ability to obtain a Top Secret security clearance.
Preferred qualifications
Experience working with frontier AI models in a software engineering context, such as:
AI coding collaboration — LLM-assisted IDEs and assistants (e.g., Cursor, GitHub Copilot, Claude, GPT-class models) for design, implementation, testing, and refactoring
MCP (Model Context Protocol) usage — connecting assistants to repositories, databases, APIs, and internal tools via MCP servers and integrations
Generative agentic programming — multi-step agent workflows, tool use, and human-in-the-loop development
Experience evaluating AI-generated code for correctness, security, performance, and maintainability
Experience defining MCP servers or agent toolchains for team or product workflows
Experience with high-performance computing (HPC) or performance-sensitive backend systems.
Distributed systems or networked service development (multi-process, multi-host communication).
GUI development experience with relevant C++ frameworks and toolkits.
Familiarity with Python and JavaScript/React for cross-stack integration where products use separate UI layers.
Experience building or consuming REST/HTTP APIs and binary data pipelines.
Background in signal-processing or DSP software (beneficial but not required).
Prior work in cleared or regulated environments.