Senior Product Manager - Platform & Automation

Relativity; Delaware; Hybrid; USD 140,000 - 210,000; Full time

Job summary

Relativity is hiring a Senior Product Manager to lead Automation Services and Infrastructure, guiding platform capabilities powering RelativityOne. You will own the roadmap, drive discovery with developers and customers, and balance scope decisions across incubation, migration, and scaled adoption.

This role emphasizes platform thinking, AI-enabled workflows, and cloud-native security. You’ll collaborate with engineering and security to maintain governance, reliability, and developer experience

Qualifications

• 7+ years in software product management across incubation, migration or adoption lifecycles.
• Experience with developer-facing or platform-facing products – APIs, SDKs, extension frameworks, or cloud infrastructure.
• Hands-on cloud platform architecture knowledge (Azure preferred) and distributed systems expertise, with AI-enabled patterns and governance awareness.

Responsibilities

• Own the roadmap and backlog; sequence work by impact, dependencies, and priorities.
• Define done criteria and maintain it across incubation to scaled adoption stages.
• Engage real customers or internal consumers early; run structured discovery with developers and ISVs to surface issues and validate ideas.
• Make hard scope decisions on what ships this quarter vs future bets; document reasoning clearly.
• Maintain velocity with a strong quality bar; ensure reliability across the platform and downstream projects.
• Balance discovery vs adoption when launching new capabilities and scaling existing ones.

Skills

Product management

Ambiguity management

APIs & SDKs

Azure cloud

AI-powered SDLC

Data-driven

Cross-functional leadership

Communication

Mentoring PMs

Tools

Azure

Job description

Job Overview

At Relativity, we build platforms that help our customers find the truth in complex data and act on it with confidence. We are hiring a Senior Product Manager to join our Automation Services and Infrastructure organization, overseeing the teams responsible for the platform capabilities that power RelativityOne. This role spans automation, critical security primitives, cloud-native infrastructure, and AI-powered extensibility: the governed operational foundation that reliably powers the agents, tools, and experiences delivering Legal Data Intelligence.

Posting Type

Hybrid

Job Description and Requirements

Own it: strong product execution across the lifecycle

• Own the roadmap and backlog. Sequence work based on customer impact, technical dependencies, and business priorities.
• Define what "done" looks like and hold to it. Regardless of whether the work is an early incubation, a platform capability driving active migration, or a mature product managing adoption at scale. The phase changes; the ownership standard does not.
• Get it in front of real customers or internal consumers early and often. Run structured discovery with developers, engineering teams, and ISVs to surface what is not working, validate what is, and generate the evidence that drives the roadmap.
• Make hard scope calls. Own the triage of what ships this quarter, what is a future bet, and what is out. Make those calls transparently, document the reasoning, and keep momentum.
• Drive velocity while holding the quality bar. Your customers - and the engineering teams that depend on your platform - need to defend their work downstream. Platform bugs compound. Hold the shipping cadence and the reliability standard together.
• Know when you are managing discovery versus managing adoption. Launching a net-new capability requires different instincts than scaling an existing one from 10% to 50% of customers. Apply the right model for where the product is, not where you wish it were.

Build the right thing: platform-first product thinking

• Define what the capability means for the developers and end users who depend on it. Platform PMs own things others build on - a wrong decision in versioning, access control, or API design compounds across dozens of teams. Build for long-term stability, not just the next release.
• Design for the human-in-the-loop. Whether in AI-driven workflows, permission management, or automation pipelines - the right escalation path, governance signal, and audit trail make operators more capable. Build for that model deliberately.
• Treat trust as a product foundation. Security, auditability, and platform governance are the moat. Partner with engineering and security to keep defensibility a first-class design constraint from day one.
• Use AI as a force multiplier. Use AI capabilities - in prototyping, research synthesis, spec drafting, and customer insight - to move faster. Model this for the team and share your innovations with the rest of the organizations because we'er all learning and in this together!

Contribute to the right ecosystem

• Define the platform patterns that scale. Working with engineering and architecture, apply the contracts and governance boundaries that let internal and external builders develop on a stable, well-governed surface. Versioning, security, capability scoping, and backward compatibility are product decisions that compound.
• Translate the platform to its builders. Turn technical concepts - cloud-native migration patterns, API security models, AI extensibility standards - into narratives that resonate with developers, domain experts, and buyers.
• Develop customer-facing documentation, enablement guides, and release notes for platform capabilities. Capture best practices from early adopters and package them into reusable assets that accelerate adoption.

Lead through influence: cross-functional and data-driven

• Be the connective tissue across product, engineering, and go-to-market for your area. Hold the picture across the development experience, runtime governance, distribution, and customer value. Pull the right people together, keep them aligned, and clear the blockers.
• Track the right metrics. Adoption, migration progress, platform reliability, and time to first successful integration. Define the leading indicators before the lagging ones catch up.
• Communicate progress and risks clearly. Report what you know, what you do not, and what you need - to your leadership, your engineering partners, and your customers.

Minimum Qualifications

• 7+ years in software product management, with demonstrated ownership across more than one product lifecycle stage - incubation, active migration, or scaled adoption.
• Demonstrated ability to deliver through ambiguity: you have defined scope under uncertainty, made hard prioritization calls, and shipped with customers in hand.
• Experience with developer-facing or platform-facing products - APIs, SDKs, extension frameworks, security primitives, or cloud infrastructure - with measurable adoption.
• Hands-on experience with cloud platform architecture (Azure preferred) and comfort in technical discussions around distributed systems, platform APIs, and cloud-native design. Working knowledge of AI-enabled platform patterns - developer tooling, agentic workflows, or AI-native services - and where reliability and governance constraints bind.
• Solid understanding of the software development lifecycle and modern delivery practices, including experience in AI-powered SDLC environments where agentic tooling is part of how the work gets done.
• Data-driven: you use data to set goals, size bets, monitor product health, and change course.
• Strong communicator across technical and non-technical audiences. You translate complex platform and infrastructure concepts into clear customer and business outcomes.
• Active user of AI tools to prototype, synthesize research, draft specs, and move faster. This is how the work gets done here.
• Comfortable working alongside or mentoring junior product managers - you've contributed to someone's growth as a PM, even without a formal reporting relationship.

Preferred Qualifications

• Background in legal technology, eDiscovery, compliance, or another domain defined by complex, high-stakes workflows where defensibility, reproducibility, and audit trails are first-class requirements.
• Experience with cloud-native platform migrations: moving workloads off legacy frameworks onto modern compute, storage, and auth primitives.
• Familiarity with emerging AI integration standards such as Model Context Protocol (MCP) or Agent-to-Agent (A2A) and how they shape platform extensibility.
• Experience building on or contributing to developer ecosystems, partner integrations, or extensibility platforms at enterprise SaaS scale.
• A technical foundation (computer science, engineering, data science, or equivalent) that lets you work credibly with senior engineers.

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 between following values:

• $140,000 and $210,000

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

Agile Methodology, Innovation, Leadership, Market Research, Market Strategy, Product Development, Product Management, Roadmapping, Team Leadership, User Experience (UX)