Lead Software Engineer - AI Surfaces

Posting Type

Hybrid/Remote

Job Overview

Relativity is a leading legal data intelligence company building technology that helps users organize data, discover the truth, and act on it with confidence. Our AI-powered, cloud platform, RelativityOne, transforms massive volumes of complex information into actionable insights for litigation, investigations, regulatory inquiries, data breach responses, and other high-stakes legal work where accuracy and trust are crucial.

The world’s largest law firms, corporations, and government agencies rely on Relativity’s legal AI software to securely surface and manage the most relevant and impactful information in their matters. Beyond our commercial impact, we are committed to expanding access to technology and supporting pro bono legal work.

WHAT WE DO

Gavel is a Microsoft Word-native agentic surface where lawyers perform real-time, evidence-based document editing and drafting. Gavel operates as a small, founder-led team within Relativity, connecting its product and engineering work with Relativity teams responsible for shared platform capabilities, identity, and security.

Job Description and Requirements

ABOUT THE ROLE

As a Lead Software Engineer, you will be the full-stack technical owner for a major area of Gavel’s product, such as a family of agents or a core capability including the context pipeline, evaluation platform, or Word integration. You will own the technical plan across the front end, harness, and data layer, along with the quality of releases and the growth of the two to four engineers building the area with you.

This is a hands-on technical leadership role. Roughly half of your time will be spent coding. You will work directly with Gavel’s CTO and Staff Engineer on architecture and represent your area to the broader Relativity technology team when it intersects with shared platform, identity, or security. The role reports to Pierre Martin, CTO of Gavel and VP of Engineering at Relativity, and may be based remotely in the United States or in Seattle or Chicago.

WHAT YOU’LL DO

· Own the technical roadmap and delivery for your area, from design through production monitoring. Break ambiguous product goals into shippable milestones and sequence them across the stack.

· Design and build agents and the infrastructure they run on, including tool definitions, prompts and context assembly, structured outputs, guardrails, evaluation sets, and the Word and web experiences that surface them.

· Run the evaluation and release loop for your agents. Understand acceptance rates, identify why results change, and determine whether a change is ready to ship.

· Model a modern software development lifecycle for your squad through small, frequent commits, feature-flagged production deployments, fast rollbacks, and daily use of agentic engineering tools to improve quality and velocity.

· Partner directly with Dorna Moini, Pierre Martin, product, and design on what to build next, and engage with customers when the answer is not clear from the data.

· Lead design reviews, establish coding and testing standards for your squad, mentor Senior and Advanced engineers, and participate in hiring.

· Work with Relativity platform and security teams on areas that touch shared infrastructure, identity, or compliance.

WHAT WE’RE LOOKING FOR

Required

· 8+ years of experience building production software in service-oriented, continuously deployed teams, including at least 1 year shipping LLM-based products or features to real users.

· Direct experience building full-stack web applications and agentic applications, including ownership of at least one agentic capability in production involving tool use and function calling, multi-step orchestration, structured outputs, retries and failure handling, and observation and debugging of non-deterministic systems.

· Practical experience with evaluation, including building evaluation sets, selecting metrics, using LLM-as-judge appropriately, and connecting offline results to online outcomes.

· A solid grasp of retrieval and context engineering, including embeddings, hybrid search, chunking and ranking strategies, and context budgeting.

· Hands-on cloud infrastructure experience with AWS or Azure, or the willingness to develop deep expertise quickly, along with comfort using containers, CI/CD, infrastructure as code, and production observability.

· Fluency in at least one of TypeScript or Python and the ability to work across the stack, including React front ends, Node or Python services, and PostgreSQL.

· Experience leading the technical work of a small team through planning, reviewing, unblocking, and developing engineers while continuing to deliver meaningful code.

· Clear written and verbal communication, including the ability to explain model-quality regressions to lawyers and scoping trade-offs to founders.

· A strong drive for simplicity and the judgment to distinguish useful abstractions from unnecessary ones.

WHY WE COULD BE A GREAT FIT

Impactful Mission

· Build systems that help customers organize data, discover the truth, and act on it in high-stakes legal matters.

Engineering at Scale

· Work on distributed, cloud-native systems that process large volumes of data.

Cutting-Edge Technology

· Build with AI, cloud platforms, and scalable architectures shaping legal tech.

Growth and Ownership

· Gain experience owning systems end-to-end across cloud and distributed environments.

Collaborative Culture

· Work in a team focused on knowledge sharing and continuous improvement.

Inclusive Environment

· Diverse perspectives create stronger teams and better outcomes.

Compensation and Benefits

· Competitive salary, benefits, DTO, parental leave, and equity program.

Relativity is committed to competitive, fair, and equitable compensation practices.

This position is eligible for total compensation which includes a competitive base salary, an annual performance bonus, and long-term incentives.

The expected salary range for this role is betweenfollowing values:

The final offered salary will be based on several factors, including but not limited to the candidate's depth of experience, skill set, qualifications, and internal pay equity. Hiring at the top end of the range would not be typical, to allow for future meaningful salary growth in this position.

Required Skills: