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About the Role
Code Metal is seeking a founding Staff Quality Engineer (SDET) for Modeling & Simulation to strengthen its Quality Engineering capabilities. This role will design and build the platform’s automated validation system, connecting and extending its foundation into reproducible quality evidence across services, models, and end-to-end workflows. You will be responsible for defining which behaviors require deterministic verification, statistical or model-based evaluation, or human review, and how limitations and residual risk are communicated as release evidence. This is a hands-on software engineering role where you will build foundational test infrastructure, write critical tests, and help engineers build quality into their work.
Responsibilities
- Translate Quality Engineering strategy into a risk-based validation approach for Modeling & Simulation across unit, integration, contract, end-to-end, performance, resilience, and security-critical workflows.
- Build reliable test infrastructure, including deterministic fixtures, isolated test data, service and event-contract tests, integration harnesses, versioned reference scenarios, deterministic replay, and focused browser automation for critical user journeys.
- Improve CI feedback through effective test partitioning, parallel execution, caching, failure attribution, and flaky-test control, in partnership with shared platform owners.
- Write behavior-focused tests for high-risk planning, sensing, simulation, authorization, state-transition, and recovery workflows.
- Partner with simulation and model owners to turn intended behavior, assumptions, and known limitations into reusable reference scenarios, regression baselines, characterization or differential tests, and reproducible quality evidence.
- Define validation and release criteria for simulation and emerging AI-assisted workflows, combining deterministic assertions, contracts, reference checks, statistical or model-based evaluation, failure-recovery testing, and appropriate human oversight.
- Establish repeatable performance and reliability validation with measurable objectives and clear release evidence.
- Participate in design and code reviews, identify testability risks early, and mentor engineers in testing complex simulation, distributed-system, and AI-assisted changes without becoming an approval bottleneck.
- Turn lessons from Modeling & Simulation into reusable quality bars, reporting practices, testing standards, and validation infrastructure for the centralized Quality Engineering function.
Requirements
- Significant experience as an SDET, test-infrastructure engineer, quality architect, or software engineer responsible for automated validation of production systems.
- Strong production programming skills in Python.
- Deep experience building Python test infrastructure using pytest or comparable frameworks, including asynchronous testing, fixtures and factories, parallel execution, and CI integration.
- Demonstrated experience designing risk-based test strategies across multiple layers of a distributed system.
- Experience validating complex systems with partially nondeterministic behavior, such as simulation, statistical models, ML, or AI-assisted workflows, and sound judgment about deterministic checks, reference evidence, statistical evaluation, and human oversight.
- Hands-on experience testing Docker-based or comparable containerized, multi-service applications, including APIs, databases, messaging, authentication, authorization, and data isolation.
- Experience building and improving CI workflows with GitHub Actions or a comparable platform, including test isolation, failure diagnosis, and flaky-test control.
- Ability to set technical direction, write design documents, mentor engineers, and lead multi-team initiatives through influence.
- Experience validating simulation, geospatial, event-driven, or other stateful systems, including reproducible deterministic and probabilistic behavior.
- Familiarity with testing or debugging C++ simulation or systems code.
- Experience testing TypeScript and React applications with Playwright or equivalent tools.
- Experience with performance testing, generated test data, and API or schema validation.
- Experience testing cloud-based, containerized systems using logs, metrics, traces, and retained test artifacts.
- Familiarity with constructive simulation, distributed simulation standards, or mission-analysis software.
- Hands-on experience evaluating AI-assisted or agentic systems, including tool-calling or multi-step workflows, and understanding risks such as nondeterminism, unsupported outputs, prompt or context manipulation, unsafe tool use, hidden state, and silent failure.
- Experience using AI coding assistants or agents throughout the software development lifecycle and defining quality controls for AI-assisted changes, such as scoped workflows, independently verifiable tests, human code review, CI checks, and risk-based release evidence.
- Experience in a regulated, high-assurance, or mission-critical domain.
- Eligible to obtain and maintain a U.S. Secret security clearance.
Skills
- Python
- pytest
- asynchronous testing
- fixtures
- factories
- parallel execution
- CI integration
- risk-based test strategies
- Docker
- APIs
- databases
- messaging
- authentication
- authorization
- data isolation
- GitHub Actions
- test isolation
- failure diagnosis
- flaky-test control
- simulation
- geospatial
- event-driven systems
- stateful systems
- C++
- TypeScript
- React
- Playwright
- performance testing
- generated test data
- API validation
- schema validation
- cloud-based systems
- containerized systems
- logs
- metrics
- traces
- constructive simulation
- distributed simulation standards
- mission-analysis software
- AI-assisted systems
- agentic systems
- tool-calling
- multi-step workflows
- AI coding assistants
- AI agents
Location
- Boston
- San Francisco
- Remote
Work Type
- Hybrid
- Remote
- Full-time
Experience Level
- Staff-level
- 8+ years of relevant software engineering, test infrastructure, or quality engineering experience
Salary/Compensations
- Pay depends on experience, but we strive to be at the upper end of the salary range
- The salary range for this role is not a guarantee of compensation or salary, as the final offer amount may vary based on factors including, but not limited to, individual proficiency, skills, experience, and location.
Benefits
- Health care plan with 100% premium coverage, including medical, dental, and vision
- 401k with 5% matching
- Paid Time Off (uncapped vacation, plus sick and public holidays)
- Flexible hybrid or remote work arrangement
- Relocation assistance for qualifying employees
About the Company
- Code Metal is the leader in automated software engineering you can trust.
- As AI writes more of the world's code, the bottleneck in software has shifted from writing code to verifying it works, and AI cannot verify its own work with certainty.
- Code Metal takes a fundamentally different approach: constrain AI to what it does reliably, verify every step independently of the model using formal methods, and keep engineers in the loop on the decisions that matter.
- The result isn't code that probably works — it's code that is provably correct, with auditable proof.
- Customers including the U.S. Air Force, L3Harris, RTX, and Toshiba use Code Metal to modernize legacy code, optimize performance on real hardware, and move prototypes to production, fast.
- Founded in 2023 with offices in Boston and San Francisco, Code Metal is funded by Accel, Salesforce Ventures, B Capital, Smith Point Capital, J2 Ventures, Shield Capital, Overmatch, RTX, and others.
- Learn more at codemetal.ai.
Equal Opportunity
- We are an equal opportunity employer.
- US Citizenship may be required for certain project assignments involving security clearance.
- Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.