software engineer, AI platform

Watershed
San Francisco, CA, United States
9 days ago
Apply on startup.jobs
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
6 years minimum
Working hours
Regular working hours
Job source

Tech stack

Clean Code Principles Artificial Intelligence Software Debugging Machine Learning TypeScript Large Language Models Model Validation Backend Build Management AI Platforms

Job description

Watershed is building the AI suite for companies to measure their emissions and decarbonize their business. We’re looking for software engineers to help build the AI platform that powers our agents product. You’ll be a technical leader laying the foundations for agentic AI at Watershed - designing the orchestration layer, controls, and tooling that let our product teams ship reliable, observable AI features on top of a wealth of operational sustainability data.

In this role you will:

  • Design and build the agent infrastructure that powers Watershed’s products
  • Develop the observability and tracing layer for agent decisions, making it possible to debug, evaluate, and improve agent behavior at scale
  • Build evals, harnesses, and guardrails that turn agent capabilities into production-grade, dependable systems
  • Collaborate with product and other AI engineering teams to set product and technical strategy, and define the boundaries between autonomous agent behavior, deterministic code, and human oversight
  • Keep up with developments and state-of-the-art in AI and agent infrastructure to determine what is relevant to Watershed
  • Work closely with Watershed product teams to contribute your expertise to build agent experiences across the product
  • Write performant, well-crafted, tested, and maintainable code across our technical stack, It starts the same for every candidate: getting to know the team members through 1 to 2 conversations about Watershed, your experience, and your interests. Next steps can vary by role, but usual next steps are a skill or experience interview (e.g. a coding interview for an engineer, a portfolio review for a designer, deeper experience call for other roles) which leads to a virtual or in person interview panel. We prioritize transparency and lack of surprise throughout the process.

Requirements

  • 6+ years of experience in backend, platform, or AI/ML engineering
  • Experience building products and infrastructure that leverage LLMs, embeddings, and other ML technologies
  • Full lifecycle experience building, deploying, and monitoring production systems that depend on LLMs or other ML technologies
  • Experience with model evaluation, agent observability, and making non-deterministic systems reliable
  • Experience building and operating production Typescript systems

Must be willing to work from an office 4 days per week (except for remote roles)

About the company

About Watershed

Watershed is the enterprise sustainability platform. Companies like Airbnb, Carlyle Group, FedEx, Visa, and Dr. Martens use Watershed to manage climate and ESG data, produce audit-ready metrics for voluntary and regulatory reporting including CSRD, and drive real decarbonization. We are looking for team members who love product-building, want to work hard at a mission-oriented startup, and will collaborate with us in shaping the culture of a growing team.

We have offices in San Francisco, New York, Denver, London, Paris, Berlin, Sydney, Mexico City, and remote team members across the US and Europe. We hope that you’ll be interested in joining us!

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on startup.jobs
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

1:52 min

Structuring and scaling the backend engineering team

Stefan Lingler Stefan Lingler +1 · Coffee With Developers

1:00 min

Misconceptions about TypeScript safety capabilities

Simone Sanfratello · JS Congress

2:36 min

Choosing between managed AI platforms and custom governance

Péter Farkas Péter Farkas · Europe 2026 Virtual

1:12 min

Choosing TypeScript for complex backend applications

Maximilian Otto Maximilian Otto · World Congress 2024

2:08 min

Essential engineering roles in the generative AI space

Mary Grygleski Mary Grygleski · LIVE

Videos

See all

Related articles

See all