Software Engineer, Frontier Data Products

Description

The company organizes human expertise to train AI models. It is a Series C company valued at $10 billion and is profitable.

The company's network includes more than 30,000 experts, who together earn over $2 million a day.

The team builds production systems that capture, coordinate and check expert work between a customer request and the final output.

These are long-running stateful systems. A job can stay active for days, mixing automated steps, model inference and expert review.

A completed step can be reopened and redone, so state must handle late changes and conflicts between humans and models.

This is backend work on distributed state machines and orchestration. The architecture is still open, and early engineers will shape it and see the effect of their work quickly.

The team works in person five days a week in San Francisco, New York City or London, and the company's new San Francisco headquarters is the base for that work.

Responsibilities

• Design services and state models for multi-stage workflows that split across automated processing and expert reviewers, then merge the results into one consistent output.
• Build orchestration pieces such as retries, failure recovery, idempotency and auditable state changes for jobs that run much longer than a single request and may need partial rework later.
• Add model inference to production workflows while keeping the system debuggable and under human oversight.
• Build the APIs and tools that let product, operations and ML teams run, debug and trust these systems at scale.
• Own reliability and monitoring for workflows where a silent failure produces a wrong result, not just an error response.
• You will build core infrastructure between customer requests and shipped outputs, not internal tooling or a support system.
• The product area is new and central to the company, so early engineers will set the architecture.
• Inputs are unpredictable. You will build durable orchestration across humans and models that may disagree deep into a multi-stage job.
• Work quickly on hard systems problems where ambiguity is normal.
• Work closely with product, operations and ML teams to turn competing constraints into a clean system design.
• Debug complex stateful workflows where failures can come from automated steps, model calls or human reviewers.
• Own your systems from design through shipping, operating and improving them.

Requirements

• Production backend experience and clear, well-reasoned views on which designs hold up over time and why.
• Strong judgment on system design, service boundaries and where complexity belongs, including when to avoid it.
• Hands-on experience with distributed systems tools: async workflows, queues, idempotency, retries and long-running jobs.
• Ability to turn unclear product, operational and ML constraints into a system that is clean and easy to debug.
• Working knowledge of Python on AWS with Postgres. Experience with Temporal or a similar workflow engine is a plus.
• You are likely someone who gets frustrated by hard-to-debug systems and fixes them.
• You have firm opinions about where state should live and can defend them in design reviews.
• You move quickly and still take ownership of reliability.
• You want your work to link quickly to outcomes that matter to customers.

Conditions

Full-time, in person five days a week.

Offices in San Francisco, New York City or London; the company's new San Francisco headquarters is the main site.

The company is an equal opportunity employer.

Benefits

• Bi-annual performance bonus structure.
• Generous equity grant vesting over 4 years.
• Relocation bonus of up to $15k.
• $10K housing bonus if you live within 0.5 miles of the office.
• $1.5K monthly stipend for meals.
• Free Equinox membership.
• $200 monthly laundry reimbursement.
• $200 monthly personal wellness reimbursement.
• Health, dental and vision insurance.