Applied AI Engineer San Francisco

Mintlify, Inc.

San Francisco, Northern (CA, KY)

Hybrid

USD 140,000 - 210,000

Full time

14 days+
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Benefits offered by this job

Competitive compensation and equity
20 days paid time off every year
401k or RRSP
$420/month wellness stipend
100% coverage for Health, dental, visI
Free Ubers to and from work
Free lunch and dinners
Annual team offsite

Job summary

Mintlify, Inc. is seeking an Applied AI Engineer to build end-to-end AI products, from agent orchestration to interfaces and back-end systems, with focus on reliability and scalable design.

You will lead production ML initiatives, iterate from experiments to production, and collaborate with customers and other engineers to raise the quality of Mintlify's AI-powered docs platform.

Qualifications

  • You have at least 4 years of professional software development experience.
  • Deep experience building production systems with language models, including agent loops, tool use, retrieval, prompting, and structured outputs.
  • Comfortable owning production software across frontend, backend, APIs, databases, and infrastructure.
  • Led complex projects from experimentation through production and thrived when defining solutions rather than following a spec.
  • Strong product intuition and care about the “why” as much as the “how” when building user-facing software.
  • Eager to talk directly with customers and use those insights to shape what we build.
  • Experience mentoring other engineers, sharing technical knowledge, and helping teammates grow.

Responsibilities

  • Building AI products end to end: Designing and shipping customer-facing AI experiences, from agent orchestration and tool use to the interfaces and backend systems that support them
  • Developing reliable agents: Building agent loops that reason over context, call tools, recover from failures, and complete long-running tasks
  • Evaluating and improving performance: Creating evals, analyzing failures, and hill-climbing on prompts, context, models, tools, and product flows
  • Shipping across the stack: Building the APIs, data pipelines, interfaces, and production infrastructure needed to turn promising prototypes into polished products

Skills

4+ years software development
Production systems with languageModels
Frontend, backend, APIs, databases
Mentoring engineers
Customer-facing software

Tools

APIs
Language models

Job description

Why Mintlify?

We're on a mission to empower builders.

  • Massive reach: Our docs platform serves 100 million+ developers every year and powers documentation for 20,000+ companies, including Anthropic, Microsoft, PayPal, Spotify, Coinbase, X, and over 20% of the last YC batch.
  • Small team, huge impact: We recently passed 65 employees and raised a $45 million Series B led by A16Z and Salesforce Ventures. Each new hire has a huge impact on shaping the company's trajectory.
  • Culture of slope over y-intercept: We value learning velocity, grit, and unapologetically unique personalities.

We grew in value faster than headcount and we’re looking to align the two quickly.

We’re looking for product-minded engineers to build the AI experiences behind Mintlify. You’ll combine strong full-stack engineering with applied AI expertise to create agents that reliably solve real customer problems.

As an Applied AI Engineer, you’ll take ownership of complex AI products from early experimentation through production. You’ll help define technical direction, establish how we evaluate and improve agent performance, and raise the quality of both our AI products and engineering practices.

What you'll work on here
  • Building AI products end to end: Designing and shipping customer-facing AI experiences, from agent orchestration and tool use to the interfaces and backend systems that support them
  • Developing reliable agents: Building agent loops that reason over complex context, call tools, recover from failures, and complete long-running tasks
  • Evaluating and improving performance: Creating evals, analyze failures, and hill-climb on prompts, context, models, tools, and product flows
  • Shipping across the stack: Building the APIs, data pipelines, interfaces, and production infrastructure needed to turn promising prototypes into polished products

What you bring to the table
  • You have at least 4 years of professional software development experience
  • You possess deep experience building production systems with language models, including agent loops, tool use, retrieval, prompting, and structured outputs
  • You are comfortable owning production software across frontend, backend, APIs, databases, and infrastructure
  • You have led complex projects from experimentation through production and thrive when defining solutions rather than following a spec
  • You have strong product intuition and care about the “why” as much as the “how” when building user-facing software
  • You’re eager to talk directly with customers and use those insights to shape what we build
  • You have experience mentoring other engineers, sharing technical knowledge, and helping teammates grow

Why you should join our engineering team
  • You’ll solve technically ambitious product problems alongside a team that values craft, speed, and thoughtful execution. Here’s a taste of what the team has built:
    • How we built a virtual filesystem for our Assistant
    • Introducing the collaborative editor built for teams and agents
    • Docs URL Benchmark: Markdown & llms.txt > HTML
  • Engineers here are product builders with high agency; you'll drive change and have a voice in strategic decisions
  • You’ll have plenty of heads-down builder time on a small-but-mighty team where the best ideas win
  • We’ll find the intersection between what excites you and business priorities. You’ll own projects, ship, and see immediate impact
Company Benefits:
  • Competitive compensation and equity
  • 20 days paid time off every year
  • 401k or RRSP
  • $420/month wellness stipend
  • 100% coverage for Health, dental, vision
  • Free Ubers to and from work
  • Free lunch and dinners
  • Annual team offsite (previously went to Alaska, Hawaii)
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