Senior Product Manager - Platform & Automation

About the role

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.

You will define product direction, establish clear product health and success indicators, and partner closely with engineering and cross-functional stakeholders to deliver resilient, secure, and scalable platform solutions. A successful candidate brings a strong technical foundation, a customer-centric mindset, and exceptional communication skills, intrinsic adoption of AI into workflow, along with proven experience leading through influence and collaborating across product, engineering, and partner teams.

Responsibilities

• 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.
  • 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 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. Document the reasoning and keep momentum.
  • Drive velocity while holding the quality bar. Ensure platform reliability to support downstream work by engineering teams.
  • Know when you are managing discovery versus managing adoption. Apply the right model based on the product’s current phase.
• Build the right thing: platform-first product thinking
  • Define what the capability means for developers and end users. Make decisions on versioning, access control, and API design that compound across teams.
  • Build for long-term stability, not just the next release.
  • Design for the human-in-the-loop in AI-driven workflows, permission management, or automation pipelines, ensuring governance and audit trails.
  • Treat trust as a product foundation. Partner with engineering and security to prioritize security, auditability, and governance from day one.
  • Use AI as a force multiplier in prototyping, research synthesis, spec drafting, and customer insight. Share innovations across the organization.
• Contribute to the right ecosystem
  • Define platform patterns that scale. Work with engineering and architecture to establish contracts and governance boundaries for stable, well-governed surfaces.
  • Translate technical concepts (e.g., cloud-native migration patterns, API security models, AI extensibility standards) into narratives for 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 to accelerate adoption.
• Lead through influence: cross-functional and data-driven
  • Be the connective tissue across product, engineering, and go-to-market for your area. Align stakeholders and clear blockers.
  • Track the right metrics: adoption, migration progress, platform reliability, and time to first successful integration.
  • Communicate progress and risks clearly to leadership, engineering partners, and customers.

Requirements

• Minimum Qualifications
  • 7+ years in software product management, with demonstrated ownership across multiple product lifecycle stages (incubation, active migration, or scaled adoption).
  • Proven ability to deliver through ambiguity: defining scope under uncertainty, making hard prioritization calls, and shipping 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 governance constraints.
  • Solid understanding of the software development lifecycle and modern delivery practices, including AI-powered SDLC environments.
  • Data-driven: use data to set goals, size bets, monitor product health, and change course.
  • Strong communicator across technical and non-technical audiences. Translate complex platform concepts into clear outcomes.
  • Active user of AI tools to prototype, synthesize research, draft specs, and accelerate work.
  • Comfortable mentoring junior product managers, even without a formal reporting relationship.
• Preferred Qualifications
  • Background in legal technology, eDiscovery, compliance, or domains with high-stakes workflows requiring defensibility, reproducibility, and audit trails.
  • 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 their impact on 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) to work credibly with senior engineers.

Pay

The expected salary range for this role is $140,000 to $210,000. The final offered salary will be based on 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. This position is eligible for total compensation which includes a competitive base salary, an annual performance bonus, and long-term incentives.