Software Engineer, Systems & Platform Applied AI

Job summary

Responsibilities

The Applied AI org builds the systems that turn human expertise into training data for frontier models, task pipelines, expert workflows, evaluation infrastructure, and the services that tie them together.

• Design, build, and operate backend services in the Applied AI stack including APIs, data models, background jobs, and the pipelines that connect them.
• Own features end to end: scope the problem, write the design, ship the code, instrument it, and keep it healthy in production.
• Build and tune high-throughput data and job pipelines: queuing, batching, idempotency, retries, and backpressure.
• Make the system fast and reliable by adding failure recovery in pipelines, profile hot spots, Agent token and cost attribution, caching issues, and set latency, error, cost…
• Instrument what you ship: observability, metrics, logging, tracing, and alerts that proactively catch problems.

What they're looking for

• 2–5 years of professional backend engineering experience building and operating production systems.
• Strong fundamentals in backend engineering: data structures, algorithms, concurrency, and writing code that's clear enough for the next person to change.
• Hands-on experience with API design - REST, gRPC, or GraphQL, and an understanding of versioning, contracts, and backward compatibility.
• Solid database skills: relational data modeling, indexing, query performance, transactions and isolation, and safe migrations.
• Practical experience with distributed systems basics: queues and event streams, caching, idempotency, rate limiting, and designing for partial failure.

Tech stack

• Terraform
• Airflow