Help build systems that discover what's wrong before it matters.
We're a small team of experts building intelligent verification systems that don't exist yet. We use the best tools, work on delightfully hard problems and let the evidence decide what's right. If this is what you're looking for, we'd like to meet you.
Agentic SQA is live today. It investigates pull requests in C codebases and reports findings with evidence a reviewer can check. It runs on real repos and is generally available. The work now is precision, adoption and coverage.
US-based. Fully remote. Cross-functional squads across AI/ML, data infrastructure, systems, compiler engineering and product development.
Explore open rolesWhat We Look For
We look for builders and scientist-engineers with deep technical ability, strong systems judgment and a bias towards proving ideas in working systems.
- • Strong depth in a core discipline
- • Willing to own problems outside your title when the product needs it
- • Clear communicator who can reason in tradeoffs and constraints
- • Bias toward building, measuring and improving
- • Comfortable being wrong fast and adjusting. We change direction when the data says to.
- • You do what you say you'll do. We don't micromanage.
If you prefer highly segmented ownership, long planning cycles before building or work that ends at the prototype, we may not be the right fit.
What We Value in Practice
Use failed experiments as data and improve quickly
For Agentic SQA, the metric is decision quality: do teams make better release decisions with our outputs than without them? We start with the metric and work backwards.
Surface risks up front, make tradeoffs explicit and take responsibility for outcomes
Move quickly without compromising instrumentation, testing or reviewability
Success is only achieved through strong collaboration across disciplines, not isolated excellence
Use the product first
Agentic SQA is live and free to try. Before you talk to us, install it and see what it does.
We are not going to tell you what to look for. Form your own view. Every conversation we have starts with what you saw, and we learn more from ten minutes on that than from an hour on your resume.
Open Roles
Apply buttons open our LinkedIn jobs page. Select the role there to apply.
Principal Product Manager – Agentic SQA
United States · Remote · Full-time · Reports to Founder and General Manager
$250,000 – $310,000 per year
This role sits at the intersection of code-intelligence depth, AI recency and product craft. You own the Agentic SQA roadmap day to day, run continuous discovery with engineers and reviewers, prototype directly in modern AI tooling and define what “good” means for a non-deterministic system through real eval harnesses. We're looking for 5+ years in product or equivalent leadership from an engineering or founder path, plus background in static analysis, program analysis, SAST, fuzzing or verification tooling.
Principal Platform Engineer – AI Ops, Backend, Reliability & Security
United States · Remote · Full-time · Reports to Cofounder and CTO
$290,000 – $430,000 per year
You own the product platform, not just infrastructure: the core services behind signup, tenancy, permissions, billing and entitlements, and provisioning. You build paved roads from feature to deploy to operate, productionize AI workloads with cost and latency under control and make reliability a system property through SLIs, SLOs and error budgets. We're looking for principal-level builder/operator experience, deep Go and/or Rust, strong Kubernetes/EKS and AWS, and security-by-design instincts.
Principal Machine Learning Engineer – Graph ML & Code Intelligence
United States · Remote · Full-time · Reports to Cofounder and CTO
$380,000 – $520,000 per year
You own the graph-ML roadmap end to end: design and train modern GNNs and graph transformers, build high-performance distributed-GPU training and inference pipelines, model code and IR as graphs and fuse graph structure with language systems for retrieval and reasoning. We're looking for 8+ years of production ML, 5+ years leading large-scale graph learning (100M–B+ edges) and strong systems chops in C++/CUDA or equivalent.
All roles are remote and flexible. Compensation includes base salary, performance incentives and benefits.
Don't see your role? Email [email protected] and tell us what you'd build.