Data Platform Engineer

TypeSafe AI
San Francisco Office, US
On-site

Who this role is best for

Data engineers with experience in production systems and internal tooling will find this role's emphasis on reliability and cross-functional collaboration compelling. The small, in-office team in San Francisco suggests a preference for hands-on contributors who thrive in close-knit environments.

Best fit for

  • Candidates with a background in building and operating large-scale data systems for AI applications
    — “rebuilding the LLM stack from first principles to make models smarter and also dependable enough to run in production”
  • Individuals who have created internal tools to support analytics and engineering teams
    — “Have experience building internal tools and supporting analytics”
  • Professionals who value craftsmanship and are motivated by high-impact, mission-driven work
    — “We strive for excellence and craftsmanship and won’t stop until we get there”

Things to consider

  • Full-time presence in San Francisco is required, with no remote flexibility indicated
    — “We work fully in person from our San Francisco office near Embarcadero station”
  • The role demands adaptability to shifting requirements and a high level of ownership
    — “Take ownership, collaborate well, and adapt to changing requirements”

How to stand out

  • Highlight experience with data orchestration and production-grade systems in your resume and interviews
    — “familiar with Kafka, ClickHouse, a data orchestrator such as Dagster or Airflow”
  • Emphasize your ability to support multiple teams and ensure data accessibility and quality
    — “Work with teams across the company to understand and support their data needs”
  • Showcase how you've contributed to engineering standards and reliability in past roles
    — “Have worked on a team with strong engineering standards”
Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • reliable data infrastructure
  • improved data quality
  • enhanced data access
Typical background
data engineeringsoftware developmentdata science

Skills & requirements

Required

Data Pipeline DevelopmentData InfrastructureData TransformationData Access ControlData Quality

Preferred

AI ApplicationsCloud Platforms

Stack & domain

Data EngineeringData InfrastructureBackend SystemsKafkaClickhouseDagsterAirflowSQLData TransformationsPermissioningBI WorkflowsOwnershipCollaborationAdaptabilityAILlms

About the role

Original posting from TypeSafe AI via Ashby

ABOUT TYPESAFE

We’re building prod, not god. TypeSafe is an AI lab pushing frontier model intelligence in a new direction, starting with System One Models. We combine the reasoning of LLMs with the reliability of code, for truly trustworthy AI. Our first model, Jev, launched in September 2026.

While others chase leaderboards, we’re rebuilding the LLM stack from first principles to make models smarter and also dependable enough to run in production. We’re a small, fast team backed by an $870M Series A led by a16z. Made in SF, with love. Come join the frontier.

ABOUT THE ROLE

You’ll build and own the data infrastructure and internal tooling that support our engineering, analytics, and business teams. You’ll work across ingestion, storage, transformations, and access controls, helping make our data reliable and easy to use.

Responsibilities include:

  • Build and maintain data pipelines, infrastructure, and internal tools
  • Support data transformations, analytical models, and BI workflows
  • Manage data access and permissioning
  • Improve reliability, performance, and data quality
  • Work with teams across the company to understand and support their data needs

WE EXPECT THAT YOU

  • Have experience in data engineering, infrastructure, or backend systems
  • Are familiar with Kafka, ClickHouse, a data orchestrator such as Dagster or Airflow, and similar technologies
  • Are comfortable with SQL, data transformations, and permissioning
  • Understand how data infrastructure supports BI and analytics
  • Take ownership, collaborate well, and adapt to changing requirements
  • Are excited about our mission and working on a small team

WE ARE HOPING THAT YOU

  • Have built and operated large-scale, production data systems
  • Have experience building internal tools and supporting analytics
  • Have worked on a team with strong engineering standards
  • Are familiar with AI and its practical applications

LIFE AT TYPESAFE

We’re a small, flat, close-knit team working to make intelligence dependable enough to become part of everyday software. We work fully in person from our San Francisco office near Embarcadero station. We love what we do and care deeply about the work.

We strive for excellence and craftsmanship and won’t stop until we get there. When the team wins, we all win, and we enjoy collaborating and inspiring each other to grow—as a team and as individuals.

We value emotional honesty, kindness, and bringing your whole self to work. We build machines; we don’t try to be machines.

We want TypeSafe to be the place where you do the most impactful work of your career and help define our future as a company.

WE PROVIDE

  • 100% covered health insurance
  • Daily lunch and dinner
  • Visa sponsorships
  • 401K plans

Source: TypeSafe AI careers (Ashby)

Similar roles