Senior Product Manager - Platform & Automation

- 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 . R egardless 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.

- Define what the capability means for the developers and end use rs 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!

- 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.

- 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.

- 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.

- 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.

The expected salary range for this role is between following values: $140,000 and $210,000

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