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Salary
$150k – $250k per year
Location
In office (San Francisco)
Seniority
Junior · 1+ year exp
Employment
Full-Time
Overview
Company
Impact
Profile match
AI agents that think in P&IDs, HMBs, and spec sheets. Torus understands every parameter across your projects and adopts how your firm works.

Gradient is everything.

Torus is building the agentic engineering tool that physical engineering firms use to build infrastructure 10x faster. We turn design engineering work that took 6 weeks into 6 hours, and we're already working with multiple Fortune 500s and major EPCs on critical infrastructure like data centers and energy installations.

Who we are

Torus was founded in May 2026 by Marcus Lima (CEO) and Rahul Thayil (CTO). Marcus previously founded Heimdal (direct air carbon capture technology and infrastructure); Oxford and Cambridge grad. Rahul previously founded Orion (AI threat intelligence and response automation). We're a team of 6 in San Francisco, with domain-specialist engineers (electrical PEs, process engineers) who make the agent think like the right engineer for each seat. We started Torus because AI can finally do the structured, geometry-heavy work at the core of reindustrialization, and the industry is burning for it.

What you'll do

You'll do it all. This is a generalist seat: you own features end to end, from ingesting messy engineering inputs (CAD, drawings, spec packages) to shipping agent-generated outputs engineers actually trust. Our north star for where your attention goes: the agent, the data substrate it reasons over, the workspaces engineers work in, and getting real outputs into partners' hands. If you're not moving one of those four, ask yourself why.

We move fast. In your first week, your code is in production. By your first month, you'll ship something used daily (e.g. an extraction pathway going from prototype to production), own an end-to-end slice for one engineering discipline, and get your work into a Fortune 500 partner's workflow.

You'll fit if you

  • Ship fast across the stack, strong Python/Rust, TypeScript (C++ a plus)
  • Have hands-on experience with PyTorch/JAX and LLM orchestration (agents, tool use, RAG)
  • Bonus: worked on CAD, robotics, simulation, geometry, or data-extraction pipelines
  • Learn fast. You don't need physical-engineering expertise, but you have to be willing to learn. Gradient is everything.
  • Willing to travel around 10% of the time to partner data center sites and energy installations to see the engineering process firsthand

Compensation

$150,000-$250,000 annual base salary, plus 0.25%-0.50% equity. The range reflects the base salary Torus reasonably expects to pay at the time of posting. The final offer will depend on job-related factors such as relevant experience, technical depth, scope, and location. Equity is subject to the applicable plan and approvals.

Benefits include medical, dental, and vision insurance; unlimited paid time off; and company-paid holidays. Benefits are subject to eligibility requirements and the terms of the applicable plans and policies.

Equal employment opportunity and accommodations

Torus is an equal opportunity employer. We consider qualified applicants without regard to race, color, religion, religious creed, ancestry, national origin, citizenship status where protected by law, age, sex, pregnancy, childbirth, breastfeeding or related medical conditions, gender, gender identity, gender expression, sexual orientation, marital status, registered domestic partner status, medical condition, genetic information, physical or mental disability, military or veteran status, reproductive health decision-making, or any other characteristic protected by applicable law.

Torus provides reasonable accommodations to qualified applicants and employees with disabilities, for pregnancy, childbirth or related medical conditions, and for sincerely held religious beliefs and practices, as required by law.

Candidates will have an initial screening followed by interviews with both founders. The process may also include a job-related technical exercise or discussion designed to evaluate the skills required for the role.

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