Applied AI Engineer

Sauna

$180K — $240K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 3+ years of engineering experience with production software
  • Experience building and deploying agent-like systems, such as multi-step LLM pipelines or scripted assistants
  • Hands-on with agent orchestration and memory management
  • Proficient in tool use and orchestration, including calling real APIs
  • Able to write production-grade code and work across systems autonomously

Responsibilities

  • Build, refine, and scale agent systems inside Sauna
  • Implement multi-step, tool-using agents with real APIs
  • Design memory systems that persist state across runs
  • Create proactive agents that send reminders
  • Own and evolve the evaluation framework for agents

Benefits

  • Meaningful early-stage equity
  • Health and dental insurance
  • 401(k) plan
  • Considerable PTO
  • Gym budget for health and wellness
  • Lunch provided regularly
Full Job Description
⚠ Please read first
  • This is a full-time, in-person role based in San Francisco (Presidio) - we work from the office 5 days a week.
  • You must be based in the Bay Area or willing to relocate before starting.
  • We require US work authorisation, but are open to O-1 or J-1 visa sponsorship for exceptional candidates.


About the Role:

As an Applied AI Engineer, you'll be responsible for building, refining, and scaling the agent systems inside Sauna, from architecture to evals to deployment.

We care about what works in production: fast response times, predictable behavior, traceability, and uptime.

You'll work across infra, frontend, and product to make sure the agents people build inside Wordware actually work.
A few examples of what you might work on:
  • Implement multi-step, tool-using agents that hit real APIs and handle retries, auth, timeouts, and edge cases.
  • Design agent memory systems that persist relevant state across runs, e.g. memory migrations, context organization, and orchestration state.
  • Create agents that proactively do work and send you reminders.
  • Own and evolve our eval framework: both automated checks and human-in-the-loop scoring.
  • Plus whatever else you see fit.
Who You Are
Minimum
  • 3+ years of engineering experience, including time shipping production software.
  • You've built and deployed agent-like systems: multi-step LLM pipelines, tool-using bots, scripted assistants, or similar.
  • Hands-on experience with:
    • Agent orchestration and memory management (e.g. memory migrations, state organization).
    • Tool use and orchestration (e.g. calling real APIs, using plugins, auth flows)
    • Evaluation: success metrics, regression testing, and improving agent behavior over time
  • You write production-grade code and can work across systems without needing a spec.
  • You'd rather ship than polish forever.
Bonus (not required)
  • Shipped agents that live in the wild, used by customers, not just internal demos.
  • Familiarity with LLM ops, tracing, observability, and failure handling.
  • You've been a founder or early engineer, and it shows in the bar you hold your own work to.

Compensation & Benefits:

Base salary: $180K-$240K + meaningful early-stage equity + health, dental, 401(k), considerable PTO, gym budget, lunch.

The Process

We keep our process simple. Exceptional candidates go from first touch to offer within 2 weeks.
  1. Application: Submit your resume and answer a few quick questions.
  2. 15-min intro call: Quick check to align on location, motivation, and logistics. If it's a go, we move fast from here.
  3. System design interview (1 hour): We dig into how you think about agent design: architecture, tradeoffs, and your experience building AI harnesses and agent systems.
  4. Technical interview (optional follow-up): A coding round testing hands-on engineering fluency and speed, only if we need a closer look.
  5. Final conversation: Answer any questions and scope out the work trial.
  6. Work trial: Paid, in-person. Typically 5 days, though we're flexible on timing depending on the role. You'll work on something meaningful with us.

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