6 hours ago
Base Salary
$140k - $230k/yr
Responsibilities
- Take a research-grade formal and agentic system to production with packaging, tests, a service interface, documentation, and a release cadence.
- Own architecture for reliability, packaging, test coverage, typing, CI, performance, observability, and release discipline.
- Wrap solver runs in agent loops while defining what agents may and may not do when proofs fail.
- Model compliance requirements, rate structures, program eligibility, design constraints, and other client business rules as mechanically checkable constraints and shapes.
- Check proposed changes against per-customer digital twins before changes reach real systems.
- Define the boundary where LLM agents may assist with translation, hypotheses, or explanations and where they cannot assert results.
- Communicate what proof results checked, what they were checked against, and what was not checked to client stakeholders.
Requirements
- At least 5 years of productionization experience taking prototype or research code into production with packaging, tests, CI, observability, and documentation.
- Deep experience with formal methods, including SMT or constraint solvers, automated theorem proving, or heuristic search over proof and planning spaces, with understanding of soundness, completeness, and practical tradeoffs.
- Experience with data modeling and shape validation, such as ontology or taxonomy design, SHACL shapes, RDF, OWL, SPARQL, or comparable knowledge-graph schema validation.
- Experience building or integrating LLM agents and understanding their failure modes around formal tooling.
- Strong Python, service-design, and generalist engineering skills.
- Practical familiarity with Z3, SMT and SAT solvers, constraint programming, SHACL, RDF, OWL, SPARQL, Python 3.12+, FastAPI, and Postgres.
- Experience with counterexample regression testing, property-based testing, and CI and release discipline for libraries.
- Working knowledge of LLM provider APIs and agent frameworks or hand-rolled agent loops.
- Bachelor’s degree required; master’s degree is a plus.
- Domain experience in energy, utilities, commercial real estate, or infrastructure is a plus.
- Must be authorized to work full-time in the United States; employment visa sponsorship is unavailable.
- Must be comfortable with a written take-home assignment followed by a live two-hour technical session.
Benefits
- Competitive early-stage startup compensation based on capabilities, experience, and location.
- Bonus eligibility and equity.
- Health insurance with meaningful dependent coverage.
- Flexible paid time off.
- Fully remote culture with a cluster of teammates in Seattle.
- Travel to company summits twice per year is required.
- Applicants may apply to a maximum of two roles at a time and must not apply to more than two roles within a six-month period.
Tech Stack
Categories
About AZX
Tech transformation, societal shifts and environmental disruption put enormous pressure on critical industries like energy, infrastructure, real estate and others to adapt, pursue new growth opportunities and optimize operations. AZX was created to meet these challenges head-on. We deliver AI transformation for critical industries providing strategy, execution and acceleration solutions. We prioritize code over powerpoint, applying start-up principles to challenge conventional thinking and develop strategic AI technology and business solutions that can be implemented quickly. We are mission-driven and client-centric, solving hard problems and building value for people, organizations and the planet. We are AZX.