Staff Software Engineer - Strategic Agentic Surfaces

Relativity is a legal data intelligence company whose AI-powered cloud platform helps users organize data, discover the truth, and act on it in high-stakes legal matters. The Staff Software Engineer will own the full-stack architecture and technical direction of the Gavel Exec agentic system, define evaluation strategies, lead the technical roadmap, drive platform and security decisions, and mentor engineers while remaining hands-on.

Responsibilities:

• Own the architecture of the Gavel Exec agent system, including dispatcher and specialist agents, tool interfaces, harness semantics, retries, structured outputs, guardrails, cost and latency budgets, and the boundary between deterministic and model-driven logic
• Set the evaluation strategy by defining quality standards for each agent, building offline evaluation infrastructure and online acceptance-rate instrumentation, and using evaluation results to gate releases
• Lead the full technical roadmap across the stack, including live indexing, hybrid search, and playbook and precedent grounding
• Drive platform decisions with Relativity, including infrastructure footprint, identity, tenancy, data residency, integration with the broader AI platform and MCP surfaces, and enterprise security requirements
• Drive a modern software development lifecycle that supports high-quality, high-velocity delivery through best-in-class agentic engineering tools and practices
• Raise the engineering bar through design reviews, pairing, and written technical direction. Mentor Lead and Senior engineers, help define the technical hiring loop, and interview senior candidates
• Remain hands-on and ship continuously, especially on the hardest and highest-leverage problems

Requirements:

• 10+ years of experience building production software, including at least 2 years shipping LLM-based products to real users and at least 5 years in a service-oriented, continuously deployed environment
• Demonstrated ownership of an agentic system in production, including multi-step tool use, orchestration across specialist components, failure handling, tracing, cost, latency, and incident response
• Deep, practical understanding of the modern AI engineering stack, including prompt and context engineering, structured outputs, function calling, retrieval, reranking, evaluation design, fine-tuning trade-offs, and model routing across providers
• Strong distributed systems fundamentals and hands-on cloud infrastructure experience, with AWS or Azure experience or a willingness to develop deep expertise quickly
• Experience with containers, CI/CD, infrastructure as code, and enterprise identity
• Fluency in TypeScript or Python and the ability to work across a React frontend, Node or Python services, and PostgreSQL
• Direct experience building full-stack web applications and agentic applications
• A track record of setting technical direction that strong engineers follow and communicating complex trade-offs clearly to product, business, and security stakeholders
• A strong commitment to simplicity and sound judgment about when abstractions add value
• Algorithms
• Automation
• Debugging
• Distributed Systems
• Performance Tuning
• Problem Solving
• Project Management
• Software Development
• System Designs
• Technical Leadership