Nuclearn.ai builds AI‑powered software for the nuclear and utility industries - tools that keep critical infrastructure reliable, efficient, and safe. Our software integrates AI driven workflow, documentation, and research automation and is already used at 60+ nuclear reactors across North America. You’ll ship production code operators and engineers rely on every day.
We’re growing quickly, expanding our team and our Phoenix HQ. The work is consequential: what you build helps real plants run safer and smarter.
Eligibility: U.S. citizenship or permanent residency (green card) is required due to DOE export compliance.
What you’ll doYou’ll own features end‑to‑end across a modern Python/React stack, with a heavy dose of reliability, data plumbing, and “meet the enterprise where it is” integration work.
- Ship production features across React (frontend) and FastAPI (backend) that power our products (e.g., CAP AI, AtomAssist).
- Design and evolve APIs and Postgres schemas for performance, correctness, and auditability (migrations, indexing/partitioning, background data corrections).
- Containerize and deploy services with Docker/Podman and Kubernetes; help tune queues/workers (Redis, RabbitMQ, Celery) for throughput, reliability and idempotency.
- Make data usable: build ingestion pipelines that prefer tabular sources (CSV/Excel/JSON) but gracefully handle the “we only have PDFs” reality - minimizing OCR, adding validation, and failing safely.
- Integrate with customer systems common in the industry (e.g., Maximo, DevonWay, Microsoft 365/Teams/OneNote).
- Own reliability: reduce noise and fix root causes identified across Sentry and Netdata; add observability, back‑pressure, retries, and circuit breakers so we never lose a record.
- Collaborate with customers: join (lightweight) customer calls with utilities to understand constraints, scope integrations, and demo new capabilities.
Reality of the role: You’ll bounce between product code, schema work, a gnarly data import, a Sentry investigation, and a customer demo environment - often in the same week.
Examples of problems you might own in your first 90 days- Build a DevonWay → CAP AI connector that ingests event data in tabular form, validates against our schemas, and supports safe reprocessing.
- Add a “simulate, then apply” workflow for CAP automations (human‑in‑the‑loop gates, dry‑run diffs, full audit trails, easy rollbacks).
- Cut a noisy Sentry class of errors by 30% by hardening a Celery task (idempotent writes, retry policy, dead‑letter queue).
- Implement license entitlements & usage reporting for a fleet customer renewal (clean server‑side enforcement plus UI visibility).
- Deliver a small Teams/OneNote POC to integrate new data streams into AtomAssist.
- Frontend: React, JavaScript, HTML/CSS
- Backend: Python (FastAPI)
- Data/Infra: PostgreSQL, SQLite; Redis, RabbitMQ, Celery
- DevOps: Docker/Podman, Kubernetes; GitHub Actions
- Observability: Sentry, Netdata (and the dashboards you help us build)
- Quality: PyTest, Cypress
- Collab: Git/GitHub
- Degree in CS or related field—or equivalent practical experience.
- You’ve shipped production React + FastAPI and can contribute independently within ~6 weeks.
- You care about correctness and safety: typed APIs, schema migrations with backfills, idempotent jobs, and tests that catch the sharp edges.
- You’re comfortable with customer‑facing engineering (a quick demo, a clarifying question, a pragmatic workaround).
- Clear, direct communicator; kind reviewer; steady under pressure.
Nice to have (not required):
- AI/ML or data‑pipeline experience (prompting, retrieval, feature stores, vector search).
- Prior startup experience.
- Exposure to nuclear/utility or other safety‑critical domains (aviation, med‑device, rail, etc.).
- CAP AI “toward 100% automation”: design safe guardrails (review gates, audit, simulation modes).
- Data connectors: unstructured PDFs, structured feeds; resilient syncs with Maximo/DevonWay; M365 integrations.
- Performance & reliability: fewer flakes, faster jobs, clearer dashboards, calmer alerts.
- Base salary: $125k - $150k (
- Equity: [–%] (meaningful ownership)
- Benefits: Unlimited vacation, health insurance, and more
- Full‑time, salaried
- Mon - Fri hybrid (Wed remote) expectation is ≥80% in‑office (Phoenix HQ)
- 20‑min intro with the founder/hiring manager to trade context and assess mutual fit
- Practical work sample (60 - 90 min; a real task in our stack)
- Team meet + peer programing (system design + collaboration)
We aim to move from first chat to decision quickly
If you want to apply modern AI and high‑quality software to problems that actually impact the future of clean energy, we’d love to meet you.
Top Skills
What We Do
With over 60 reactors around the world relying on our technology, Nuclearn is built on one simple idea: nuclear deserves better tools. Our team—made up of nuclear professionals and engineers—set out to modernize the industry by applying AI to some of its most critical, and often outdated, processes.
“We saw this massive gap,” said Bradley Fox, CEO and co-founder. “You’ve got the tech to split atoms, but a lot of the supporting work is still done with decades-old systems. We knew AI could help streamline that complexity—making things safer, faster, and more efficient. It’s a win for the plants, and for the future of clean energy.”
Jerrold Vincent, our CFO and co-founder, adds: “Back in 2016, we recognized the potential for AI to support nuclear—not just in cutting costs, but in preparing the next generation of workers. That’s why we started Nuclearn. We believe AI is one of the best tools we have to keep nuclear strong for the long haul.”
The software we’ve built isn’t generic. It’s nuclear-specific, pre-trained, and ready to go—designed by people who’ve lived the process and know exactly what this industry needs.
