# Staff Software Engineer - Kilo Code at Anaconda

- Company: Anaconda
- What the company does: About Anaconda Be at the center of AI Anaconda is built to advance AI with open source at scale, giving builders and organizations the confidence to increase productivity, and save time, spend and risk associated with open source. Backed by Insight.
- Company website: https://www.anaconda.com/
- Type: Startups
- Level: Senior
- Location: Remote (United States)
- Work setup: Remote
- Pay: $200K to $260K base salary per year (USD)
- Posted: 2026-09-01
- Apply by: 2026-10-16
- Apply: https://ats.rippling.com/anaconda/jobs/ce25432a-93ac-4018-b701-600866ac3391
- Page: https://www.1752.vc/careers/jobs/anaconda-staff-software-engineer-kilo-code/

## About the role

We're looking for a Staff Software Engineer to lead the evolution of Kilo Code, our flagship VS Code extension with over 5 million downloads processing more than 10 trillion tokens per month. You'll join a 15-person engineering team (average 10+ years of experience) working on one of the most-used AI-assisted coding tools in the world. You'll ship your first PR on day one and have hands-on ownership of high-impact features at the velocity we expect from everyone on this team.

## What they're looking for

- Set technical direction for performance optimization initiatives across startup time, memory footprint, and CLI communication, establishing patterns and instrumentation that the team can leverage
- Design, build, and ship advanced features including granular auto-approval rules, context optimization, and Smart Apply workflows, then extract the patterns so the team can reuse them
- Drive cross-team initiatives that span the extension, backend services, and AI infrastructure, translating business priorities into technical roadmaps and breaking down complex problems into shippable increments
- Mentor engineers on the team through code review, architectural discussions, and pairing sessions, raising the bar for code quality, testing practices, and performance rigor
- Own end-to-end delivery of high-impact features from technical design through production deployment, including rollout strategy, telemetry design, and post-launch iteration based on user feedback
- Establish engineering standards for AI coding workflows including context window optimization, token compression strategies, and chat interface patterns that serve 6T+ tokens per month

Tags: Engineering