Product Owner

At Epiq , your work contributes to complex, global legal outcomes. You’ll join a values‑driven community where integrity guides decisions, relentless service sets the bar, and we thrive on big challenges together. We invest in your growth with enterprise‑wide learning and mobility. We celebrate who you are, and we respect life beyond work with flexibility that’s recognized externally. Enabled by modern platforms and AI, you’ll do the most meaningful work of your career and see your impact at scale. Job Description: Job Summary As a Product Owner you are the primary link between stakeholders and delivery teams, balancing business priorities, customer expectations, operational realities, and technical feasibility. You will work closely with CTO’s org, Engineering Leadership, product management and cross-function teams. The role calls for a highly motivated, independent thinker who is organized, detail-oriented, adaptable, and effective at building relationships across diverse teams and stakeholder groups. Maximize product value by owning the definition, prioritization, and delivery of product capabilities — translating customer, business, operational, and regulatory needs into clear, actionable requirements and measurable outcomes. Essential Job Responsibilities Product Vision, Strategy & Roadmap

• Define and communicate a product vision aligned with Epiq's strategic objectives and client needs.
• Create, maintain, and prioritize the product roadmap to deliver maximum business value.
• Partner with Product Management and Senior Product Owners to align delivery priorities with the broader product strategy.
• Define minimum viable products, experiments, and incremental delivery approaches that get value to business and customers early. Backlog Ownership & Agile Delivery
• Own, maintain, and continuously refine the product backlog, prioritizing on value, risk, dependencies, and technical feasibility.
• Translate business needs into epics, features, user stories, acceptance criteria, and functional requirements. Lead backlog refinement and participate in sprint planning, reviews, retrospectives, and release planning.
• Provide day-to-day requirement clarification and timely product decisions to engineering, QA, and UX, resolving impediments as they arise. Hands-On AI Fluency & Tooling
• Use AI tools hands-on in daily product work — requirement drafting, story refinement, discovery synthesis, research, meeting summarization, usage analysis — and maintain reusable prompt patterns for those workflows.
• Stay current on AI capabilities and emerging patterns, and translate that awareness into concrete product decisions.
• Build lightweight prototypes and clickable concepts using AI-assisted and low-code tools to validate ideas before committing engineering capacity.
• Identify and prioritize AI use cases on customer value, feasibility, data readiness, risk, and measurable impact, including where AI can remove manual effort from operational and client-facing workflows.
• Define evaluation criteria for AI-enabled features — accuracy, groundedness, latency, cost, confidence thresholds — with human-in-the-loop checkpoints and fallback paths for non-deterministic output.
• Ensure AI usage meets privacy, security, client-confidentiality, auditability, and responsible-use requirements, and never treat unvalidated AI output as a final decision or deliverable. Stakeholder & Customer Leadership
• Serve as the voice of the customer and the liaison between business stakeholders, technical teams, operations, and clients.
• Gather and document business and customer requirements, and facilitate discovery workshops, demonstrations, and feedback sessions.
• Convert customer feedback, usage trends, and operational insight into actionable backlog changes.
• Communicate priorities, roadmap progress, delivery status, risks, and key decisions with clarity.
• Build trusted relationships and influence decisions across organizational levels, from delivery squads to senior leadership. Quality, Risk & Continuous Improvement
• Embed security, privacy, compliance, information governance, and operational readiness into the product lifecycle.
• Identify and communicate delivery risks, assumptions, dependencies, and constraints early.
• Define success metrics and track adoption, utilization, and business value to guide roadmap and investment decisions.
• Support product documentation, release communications, and enablement materials.
• Validate delivered functionality, lead feature acceptance, and support UAT, release readiness, and deployment. Qualifications, Requirements & Skills Education
• Bachelor's degree in Business, Information Systems, Engineering, Computer Science, or a related field, or equivalent practical experience.
• Advanced degree, or a product management certification (CSPO, PSPO, SAFe PO/PM, CSM, or equivalent). Experience
• 7+ years as a Product Owner, Product Manager, Business Analyst, Product Analyst role.
• Proven delivery in Agile or Scrum environments, owning enterprise software or SaaS backlogs.
• Demonstrated ability to elicit requirements and translate complex business needs into user stories and acceptance criteria.
• Hands-on experience with backlog & delivery-management tools
• Azure DevOps (Preferred), Jira.
• Practical, day-to-day use of AI tools in product, analysis, or delivery work, with specific examples of how they changed your output or decisions.
• Strong stakeholder engagement across business and technology teams, with excellent written and verbal communication.
• Experience defining, launching, or scaling AI or machine-learning-enabled product features in production.
• Added Advantage
• Experience with document capture, classification, data extraction, or workflow automation technologies.
• Experience supporting global stakeholders and distributed development teams.
• Experience running structured pilots or proofs of concept with emerging technology vendors. Product Ownership
• Backlog management and value-driven prioritization
• Requirements elicitation, analysis, and functional documentation
• Roadmap planning and product lifecycle support
• Business process analysis and process improvement AI Adoption
• Applied AI literacy: LLMs, prompt engineering, retrieval-augmented generation, agentic and automation workflows
• AI-assisted document classification, summarization, and intelligent data extraction
• Evaluation and quality criteria for non-deterministic features, including human-in-the-loop design
• Responsible AI: data privacy, security, confidentiality, auditability, and bias awareness
• AI-assisted prototyping and low-code or no-code tooling
• Software development lifecycle knowledge; comfort with APIs, integrations, cloud applications, and enterprise architecture
• Data analysis and metrics interpretation; self-sufficient with dashboards and queries Collaboration & Personal Effectiveness
• Stakeholder management and relationship building across varied personalities and communication styles
• Cross-functional influence without authority
• Independent thinking, self-motivation, ownership, and accountability
• Adaptability and comfort with changing direction in a fast-paced environment
• Organization, attention to detail, and structured problem solving
• Customer-first mindset and sound judgment under ambiguity
• Curiosity and continuous learning — particularly in a field moving as quickly as AI Domain Knowledge (Good to Have)
• Experience in Legal Technology, eDiscovery, Compliance, Information Governance, Digital Forensics, Data Breach Response, Court Reporting, records or content management, or Professional Services.
• Document capture solutions, records management, Enterprise content management and workflow automation Success Measures You may be assessed on the critical capabilities relevant to success in this role, including:
• Product vision development and strategic roadmap execution
• Timely delivery