AI Engineer

Momentic, Inc.; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health insurance

401(k)

Unlimited PTO

Company holidays

Lunch provided

Commuter benefits

Team offsites

Job summary

Momentic, Inc. is seeking an hands-on AI engineer to fine‑tune models, build evaluations, and turn production data into more reliable agents. You will work closely with the CTO to improve the models behind Momentic's AI-native testing platform, impacting testing and browser workflows with real production data.

You’ll design repeatable experiments, publish benchmarks, and own technical projects from idea to delivery, partnering with the engineering team to trade off practicality and performance.

Qualifications

• 3+ years of software engineering experience with hands-on AI-powered capabilities.
• Hands-on supervision fine-tuning, training data prep, and evaluating model behavior.
• Experience with prompt and context tuning, evaluation datasets, and LLM observability.
• Strong engineering fundamentals; write efficient code and recognize growth areas.
• Experience using AI agents to build software and guide agents when blocked.
• Comfortable working autonomously in ambiguous environments.

Responsibilities

• Fine-tune models for long-running agents and diagnose failures from infra, code changes, or authorship.
• Build and curate training/evaluation datasets from production workflows.
• Develop LLM evaluations and observability linking offline results to production behavior.
• Tune prompts, context, and model behavior to improve reliability and cost.
• Design repeatable experiments and publish benchmarks for core agents' performance.
• Own technical projects from problem definition to delivery with the team.

Skills

AI engineering experience

Fine‑tuning models

Prompt tuning

LLM observability

Production data analysis

Software engineering fundamentals

Job description

Momentic is building the definitive verification layer for software: an AI-native testing platform that helps engineering teams catch bugs before they ship. As AI accelerates software development, teams need a reliable way to verify that their products work. Engineering teams at Notion, Webflow, Xero, and Whatnot use Momentic to ship with confidence.

You’ll join our engineering team and work closely with our CTO to improve the models and agents behind Momentic. We’re looking for a hands‑on AI engineer who can fine‑tune models, build evaluations, and turn production data into more reliable, efficient agents. Momentic executes more than 1 million tests daily and processes more than 1 billion tokens per hour at peak, giving your improvements a direct impact on the product.

What you’ll do

• Fine‑tune models for long‑running agents, including agents that investigate whether test failures come from infrastructure, recent code changes, or test authorship.

• Build and curate training and evaluation datasets from production workflows, using failure patterns to identify opportunities for improvement.

• Develop LLM evaluations and observability that connect offline results with production behavior and help the team verify improvements.

• Tune prompts, context, and model behavior to improve task success, reliability, latency, token usage, and cost.

• Design repeatable experiments and help publish benchmarks that demonstrate our core agents’ performance on testing and browser workflows.

• Own technical projects from problem definition through delivery, working with the engineering team to make practical tradeoffs and ship improvements.

You’re perfect for this role if…

• You have relevant software engineering experience, typically 3+ years, including hands‑on contributions to AI‑powered capabilities used in production.

• You have hands‑on experience with supervised fine‑tuning, including preparing training data and evaluating model behavior.

• You’ve worked with prompt and context tuning, evaluation datasets, and LLM observability to diagnose failures and measure improvements.

• You have strong engineering fundamentals, code efficiently, and know what you’re great at and where you have room to grow.

• You use AI agents to build software, breaking down work, tracking progress, checking results, and redirecting agents when they get stuck.

• You’re comfortable with autonomy and ambiguity. You can turn an unclear problem into a plan, manage your own work, and follow through to delivery.

We’re interested in the depth of your contributions and what you’ve shipped. Your experience may come from owning an AI capability within a larger product.

Nice to haves

• Experience with reinforcement learning fine‑tuning, or LLM‑as‑judge evaluators.

• Experience with long‑running agents, recovery from failed steps, or coordinating multiple agents.

• Experience publishing benchmarks or running rigorous experiments on AI systems.

About us

• Raised a $15M Series A led by Standard Capital, with backing from Y Combinator, FCVC, Transpose Platform, and Dropbox Ventures.

• Our customer base has grown 4 year to date.

• A team of 17 and growing.

• Based in person in San Francisco at 650 5th Street.

Benefits

• Medical, dental, and vision insurance.

• 401(k).

• Unlimited PTO and sick days, plus company-observed US holidays.

• Daily lunch and a fully stocked kitchen.

• Commuter benefits.

• Team offsites and events.