Full Stack Developer Jobs in Santa Fe, NM (NOW HIRING)

How do you turn a decades-old dataset into an industry-leading medical coding agent? Teach an AI receptionist to book appointments in Spanish? Automatically generate working data connectors from API docs? Build agents that write, test, and deploy their own software packages?

Anthropic is defining frontier AI. Ode is the team bringing frontier technology into practice.

We are a team of experienced builders who care deeply about getting complex AI systems into production, with strong conviction about what makes them succeed. As Anthropic’s services venture, we tackle the hardest, most consequential AI problems for companies with real stakes, working closely with their Applied AI and Product teams to turn frontier technology into real world impact.

We're backed by Anthropic, Blackstone, Hellman & Friedman, Goldman Sachs, General Atlantic, Leonard Green & Partners, Apollo Global Management, GIC, and Sequoia Capital.

We're headquartered in SF with offices in NYC, Raleigh-Durham, and Dubai.

Our customers come to us with ambitious, often fuzzy goals — make content moderation faster, customer service cheaper and better, unlock new integrations, automate the workflows no one else can touch.

Your job is to help turn those goals into AI-powered solutions that work in the real world. You'll work closely with experienced team members while ramping to own parts of projects end-to-end. Ownership scales with performance: you'll take on more responsibility, including running projects, as soon as you demonstrate you're ready. You'll be expected to grow into independently running projects within 12–24 months.

This is a forward-deployed, full-stack customer role:

• Part engagement manager — you build trust quickly and own day-to-day with the client.

• Part product manager — you help drive what we build and why.

• Part delivery/program manager — you run the execution motion.

• Part operator — you jump into the gaps to keep things moving without waiting to be asked.

You’ll work on small engineering pods (2–5 engineers and a senior PM), shipping multiple AI products every year.

You’ll take ownership of execution and delivery operations while building toward full ownership of end-to-end projects.

• Own the customer relationship. Build strong day-to-day relationships with customers and grow into a trusted partner. Join early-stage calls, run discovery, synthesize feedback, and set clear expectations across all levels of the organization.

• Shape what we build and why. Contribute to defining product builds, refining scope, and identifying high-leverage use cases. Translate ambiguous business problems into crisp problem statements, user journeys, and success metrics.

• Turn messy problems into shipped solutions. Translate ambiguous needs into clear requirements, PRDs, and plans for engineers. Shape workflows, edge cases, and evaluation criteria for AI-powered systems.

• Drive execution across multiple AI products. Increase team leverage by owning delivery mechanics — tracking progress, coordinating stakeholders, running the day-to-day rhythm, and proactively flagging risks with clear recommendations.

• Help create demand, not just fulfill it. Jump on early, messy conversations where the project is still a vague idea. Help founders and sales tease out real pain, sketch solution approaches live, and spot expansion opportunities.

• Drive adoption and long-term impact. Work with client teams on rollout, enablement, and change management so the systems you build actually get used. Bring back insights that inform Ode's playbooks and product direction.

• Bring judgment and clarity. When requirements are fuzzy or customers change course, help drive toward the highest-impact solution and be the person in the room who can say: here's what we're trying to do, here's what we know, here's the plan.

• Customer-facing experience under pressure. You’ve taken meaningful ownership in projects where customers were stressed, stakeholders weren’t aligned, and the path wasn’t obvious. You’re comfortable pushing back, reframing problems, and holding the line on quality. We typically look for 1–3 years in product, consulting, or implementations, although we care more about what you’ve done than the label on your resume.

• Real delivery experience. You’ve built and shipped products with engineers and designers, ideally across multiple cycles. You can run an execution rhythm — stand‑ups, planning, tracking, retros — without turning it into process theater.

• Structured problem-solving and communication. You ask good questions, structure chaos, and turn ambiguity into a plan — moving from whiteboarding with execs to writing a crisp doc for engineers without losing the plot. You explain ideas simply, avoid jargon, and tie your work directly to business value.

• Bias for action and ownership. You roll up your sleeves and make things happen, whether that’s writing a scrappy SQL query, drafting a support playbook, or jumping into a last‑minute exec demo.

• Comfort with ambiguity and intensity. You like high‑energy environments, messy problems, and “we haven’t done this before” projects. You can juggle multiple customers, keep priorities straight, and make good calls with incomplete information.

• AI curiosity, not AI dogma. You don’t need deep AI expertise on day one — you do need strong reasoning, a desire to learn fast, and a willingness to overuse AI in your own workflow.

A typical PM here ships two to three products per year and learns from dozens more. You have outsized autonomy on each product — but you won’t have a year to polish a single system. The upside is constant time on the frontier of models and tooling, and a muscle for AI product development that’s hard to build anywhere else.

Many PMs look back at this as the biggest growth period of their career. But it’s possible you won’t like it — we recommend using the interview process to hear what our team members think.

• Overdeliver: We are writing the playbook on how to create enterprise value with LLMs, and building our reputation as the world’s best applied AI team.

• Overuse AI: We go out of our way to experiment with the latest tools and share what we learn with our teammates - building a culture at the frontier.

• Over "engineer" the culture: For every big decision, we ask “would this make Ode a better or worse place for our team?”

San Francisco, CA

Work Arrangement: 4 days in-person, Fridays remote

• Competitive Compensation Package: Attractive salary aligned with your experience and skills.

• 401k with Matching: Invest in your future with our company-matched retirement plan.

• Unlimited PTO: Take the time you need to relax and rejuvenate.

• Exceptional Medical, Dental, and Vision Coverage: Comprehensive health benefits to keep you and your family healthy.

• Health FSA: Manage out-of-pocket health expenses effectively.

• Commuter Benefits: Make your travel to work easier and more affordable.

• Life Insurance: Providing peace of mind for you and your loved ones.

• Team Events and Activities: Regular events to build camaraderie and a strong team spirit.