Mozilla Corporation is a non-profit-backed technology company that aims to improve the internet for users worldwide. They are seeking a Senior Staff AI & Agentic Systems Engineer to lead the architectural design and implementation of next-generation AI agent frameworks and workflows within a fast-paced team.
Responsibilities:
- Architect Agentic Systems from Zero: Design and deploy production-grade multi-agent frameworks, complex orchestration layers, and custom AI developer tooling
- Balance Speed and Scale: Navigate the tension between rapid prototyping and long-term sustainability, knowing exactly when to cut corners to validate a concept and when to slow down to lay rock-solid architectural foundations
- Orchestrate LLM Workflows: Navigate and integrate various commercial and open-source large language models, selecting and optimizing the right models for specific agentic behaviors
- Accelerate with AI Tooling: Lead by example by extensively leveraging advanced AI coding tools to maximize velocity, while establishing best practices for AI-assisted engineering across the team
- Drive Evaluation and Performance: Implement rigorous frameworks for benchmarking, prompt engineering, and evaluating agent reliability, latency, and accuracy
- Collaborative Technical Leadership: Set engineering standards for code quality and system performance, mentoring other engineers and acting as a primary bridge between research and product
Requirements:
- 7+ years of professional software engineering experience, particularly in fast-paced environments where you've shipped complex systems from scratch
- A proven ability to judge technical debt. You know how to ship an MVP in days, but you also know how to design a clean API boundary so that early speed doesn't block future scale
- 2+ years of direct, hands-on production experience specifically building autonomous workflows, custom tools, and agentic systems
- Deep familiarity with diverse LLMs and orchestration frameworks (e.g., LangChain, LangGraph, CrewAI, AutoGen, or similar tools)
- Prior early-stage startup experience, meaning you are comfortable with ambiguity, pivot quickly based on data, and focus heavily on execution
- Deep, everyday proficiency building software with advanced AI coding tools (such as Cursor, Copilot, or custom LLM extensions) to radically speed up delivery
- Comfort writing clean, high-performance code in languages like Python or Go, with a solid grasp of distributed backend systems
- Experience building developer-facing products, SDKs, or open-source libraries
- Prior contributions to open-source AI or agent frameworks
- Experience with vector databases and retrieval-augmented generation (RAG) at scale