Engineering Lead - Agents

About the role

ABOUT 8090

Enterprise software has become too expensive, complex, and difficult to change. Co-founded and led by Chamath Palihapitiya, 8090 is building a Software Factory that orchestrates the end-to-end SDLC and delivers fully managed, hosted software built for each customer's needs. We are a lean team building the technology to fundamentally change how software gets made.

ABOUT THE ROLE

We are hiring an Engineering Lead to drive the technical direction and execution of the Software Factory agent. This is a builder-leader role combining deep agent expertise with the ability to build and scale an exceptional engineering team. You will stay hands-on in the code while working with product management to turn ambitious capabilities into dependable customer experiences.

LOCATION

You will work in person five days a week from our Redwood City, CA office.

RESPONSIBILITIES

- Technical Direction: Own agent architecture across multi-agent orchestration, agent harnesses, prompt and context design, retrieval-augmented generation (RAG), memory, tools, and execution environments. Lead architecture reviews and make tradeoffs between capability, complexity, latency, and cost.

- Prioritization and Execution: Work with product management on agent capabilities and user experience, then own engineering delivery. Translate the shared roadmap into technical plans, milestones, and dependencies; focus the team on the highest-impact work and remove blockers.

- Hands-on Engineering: Regularly write and ship production code, lead code reviews, and solve difficult technical problems alongside engineers. Build capabilities for reasoning about code, working across repositories and development tools, and interacting with browsers and computer environments.

- Engineering Leadership and Mentorship: Develop engineers' technical judgment, help recruit exceptional talent, and establish effective planning and review practices. Clarify ownership, resolve technical disagreements, and build a team that coordinates well and takes accountability for outcomes.

- Production Performance: Make agent behavior observable and debuggable, with reliable recovery and escalation when tasks fail. Use production traces, experiments, and customer feedback to improve task completion, output quality, reliability, latency, and cost. Make progress and tradeoffs visible to leadership.

- Safe Deployment: Partner with security and infrastructure engineers on permissions, sandboxing, data boundaries, and controls for deploying and operating agents in production.

REQUIRED SKILLS

- A record of shipping production agents with sustained, high-volume usage and measurable customer impact. You can explain the decisions you owned, the failures you encountered, and the improvements you delivered.

- Deep practical expertise in LLM-based agent systems, including orchestration, context engineering, tool integration, memory, model selection, and evaluation.