Lead Software Engineer, Platform

Reducto is the agentic document platform for leading AI teams who demand enterprise performance at scale. We provide a comprehensive toolkit for working with documents the way a human would, combining custom in-house and leading frontier models to power efficient and accurate document workflows.

We’ve grown rapidly, increasing revenue 8x year over year and partnering with hundreds of companies, from leading AI teams like Harvey, Vanta, and Scale, to enterprise customers across FAANG and top trading firms.

Reducto has raised over $100M from world-class investors including a16z, Benchmark, and First Round Capital.

As the Lead Software Engineer on Platform, you’ll own the infrastructure behind Reducto’s core API: the systems that make document understanding fast, reliable, and cost-efficient at scale. You’ll work across Python services, queues, model-serving paths, Kubernetes/container infrastructure, observability, and developer tooling to make Reducto’s platform increasingly bulletproof as usage grows.

This is a high-leverage infra role. The ideal person has built and operated real production systems, cares deeply about latency/reliability/cost, is comfortable leading technical direction for a small team, and uses modern LLM coding tools fluently to move faster.

• Have 5+ years building, hardening, and scaling production backend/platform systems.

• Have hands-on experience with distributed systems, Kubernetes or similar orchestration, cloud infrastructure, observability, and incident-driven reliability work.

• Are strong in Python, or deeply expert in another backend language and excited to work primarily in Python.

• Have used Terraform/IaC, containerized deployments, and production debugging workflows.

• Are highly fluent with LLM coding tools such as Claude Code, Codex, Cursor, or similar, and use them as part of your daily engineering loop.

• Have led projects or small teams, raised engineering quality, and can communicate clearly with founders, engineers, and occasionally customers.

• Scaling Reducto’s core API and document processing pipelines for higher throughput and lower latency.

• Reducing infrastructure and model-serving costs without sacrificing quality or reliability.

• Improving Kubernetes/containerized deployment workflows, observability, alerting, and operational safety.

• Building internal tooling, evals, and debugging workflows that help engineers find and fix failures quickly.

• Partnering with ML/backend engineers to optimize LLM/model-serving paths in production.

• Acting as a technical lead for platform/backend projects as the team grows.

• Have built infrastructure at an early-stage or high-growth startup.

• Have worked on AI infrastructure, model-serving, agent platforms, developer tools, or high-throughput APIs.

• Have meaningful experience with Terraform, Kubernetes, queues, Postgres, observability, or cloud cost optimization.

• Are comfortable talking with customers or translating customer pain into platform improvements.

• Keep up with modern AI/LLM tooling and actively use it to improve your engineering workflow.

This is an in person role at our office in SF. We're an early stage company which means that the role requires working hard and moving quickly. Please only apply if that excites you.