Responsibilities
- Work with domain experts across CRA’s practice areas to identify, structure, and prioritize AI and digital product opportunities
- Facilitate discovery sessions, user interviews, stakeholder workshops, and user story mapping sessions with consultants, corporate staff, data experts, and engineering teams
- Translate complex consulting workflows into clear product requirements, user personas, user journeys, epics, user stories, acceptance criteria, and success metrics
- Develop business cases for proposed AI and digital initiatives, including expected user value, business impact, required resources, adoption considerations, risks, dependencies, and sequencing
- Help distinguish between ideas that should become enterprise products, practice-specific tools, reusable accelerators, vendor-enabled solutions, or one-off project assets
- Create and maintain product roadmaps, prioritized backlogs, release plans, sprint plans, decision logs, and delivery artifacts that technical teams can execute against
- Clarify scope, minimum viable product definitions, release criteria, dependencies, decision rights, and definitions of done
- Convert ambiguous stakeholder needs into actionable work while preserving the business context and analytical standards that matter to CRA’s practices
- Balance near-term delivery needs with longer-term platform strategy, reuse, governance, maintainability, and enterprise adoption
- Define measurable outcomes and product health indicators such as adoption, usage, quality, cycle time, stakeholder satisfaction, and business impact
- Run agile delivery processes across cross-functional teams, including sprint planning, backlog refinement, daily standups, sprint reviews, retrospectives, release planning, and cross-team dependency management
- Maintain delivery visibility through burn-down or burn-up reporting, RAID logs, dependency maps, release dashboards, and concise executive-ready status updates
- Ensure teams have clear priorities, well-formed stories, acceptance criteria, aligned sprint goals, and a shared understanding of tradeoffs
- Remove blockers by coordinating across practice stakeholders, engineering, data science, IT, security, legal, risk, vendor, and leadership groups
- Adapt agile practices to CRA’s consulting environment, where work may include internal R&D, client-facing delivery, practice-led prototypes, enterprise infrastructure, and rapidly evolving AI capabilities
- Serve as the connective tissue between senior stakeholders, practice experts, technical teams, and corporate functions
- Facilitate structured decisions when stakeholders have competing priorities, unclear ownership, unresolved risks, or differing definitions of success
- Help establish governance routines for intake, prioritization, delivery readiness, launch readiness, adoption, and continuous improvement of AI and digital products
- Support responsible AI, confidentiality, model validation, data governance, regulatory sensitivity, and quality control requirements throughout the product lifecycle
- Ensure that product documentation, meeting artifacts, action items, and delivery commitments are crisp, traceable, and easy for busy teams to act on
- Plan demos, pilot programs, beta feedback loops, launch communications, training materials, adoption support, and post-release reviews
- Collect feedback from consultants and corporate users and translate it into prioritized enhancements, usability improvements, and process changes
- Track delivery metrics and product outcomes, then use those insights to improve team performance, product quality, and stakeholder confidence
- Continuously refine agile processes, product artifacts, and team rituals so they remain lightweight, useful, and appropriate for CRA’s culture
- Help build a repeatable operating model for taking AI and digital ideas from intake through discovery, delivery, release, adoption, and measurable impact
Requirements
- Bachelor's degree in Software Engineering, Engineering, Product Management or related discipline, advanced degree welcomed
- 5-8+ years of experience in product management, agile delivery, scrum leadership, business analysis, digital transformation, AI product operations, or technology-enabled consulting
- Demonstrated experience translating ambiguous business needs into structured requirements, user stories, acceptance criteria, roadmaps, release plans, and delivery plans
- Hands-on experience running agile ceremonies and managing cross-functional product backlogs in Jira, Azure DevOps, or comparable tools
- Experience working directly with senior stakeholders, subject matter experts, software engineers, data scientists, IT/security teams, and legal/risk stakeholders
- Ability to communicate effectively across both technical and non-technical audiences, including senior executives, consultants, product teams, and engineering teams
- Strong documentation discipline and ability to create concise artifacts that clarify decisions, scope, risks, dependencies, and next steps
- Proven ability to remove blockers, manage dependencies, drive accountability, and keep teams aligned without relying solely on formal authority
- Strong judgment in environments where confidentiality, quality control, client impact, and responsible use of technology matter
Nice to Have
- Experience with AI-enabled products, generative AI, knowledge management tools, internal copilots, RAG applications, analytics platforms, workflow automation, or enterprise data products
- Experience in consulting or professional services, especially environments where senior experts own client relationships and delivery standards
- Experience supporting product development in regulated, confidential, or high-stakes contexts such as litigation, life sciences, healthcare, financial services, energy, economics, or legal services
- Experience with tools such as Jira, Azure DevOps, Confluence, Aha!, Productboard, Miro, Mural, Monday.com, Smartsheet, Microsoft Planner, Teams, SharePoint, or similar platforms
- Scrum Master certification, Product Owner certification, SAFe certification, or equivalent practical agile experience
- Familiarity with responsible AI principles, model validation, AI risk management, data governance, information security, and enterprise AI adoption
- Comfort working with technical product concepts such as APIs, cloud platforms, data pipelines, LLM routing, authentication, usage tracking, and software release lifecycles
Benefits
- Comprehensive total rewards program including a superior benefits package
- Wellness programming to support physical, mental, emotional and financial well-being
- In-house immigration support for foreign nationals and international business travelers
- Robust skills development programs including formal and informal training
- Technical training, presentation skills, internal seminars, career mentoring and performance coaching from an assigned senior colleague
- Leadership and collaboration opportunities through internal firm development activities
