Role Description We’re looking for a Sr. Technical Project Manager (TPM) to drive delivery for complex, cross-functional initiatives—including those involving AI/ML and intelligent automation. You’ll balance scope, timeline, and dependencies while partnering across Engineering, Product, Data, Security, and Operations to deliver high-quality outcomes. This role is ideal for someone who can run tight execution rhythms and understand the unique delivery needs of AI work in the rollout of the AI-Driven SDLC (AIDLC). What You’ll Do - Own end-to-end project execution: plan, schedule, and drive delivery across the full project lifecycle, balancing constraints and keeping work moving forward in partnership with product and engineering counterparts. - Build and maintain project plans, track milestones, and proactively manage risks, issues, and tradeoffs—providing clear stakeholder updates with recommended solutions. - Serve as the PMO lead for the ML's agentic platform and customer-facing products — the structured methodology for developing, testing, deploying, and operating AI agents within MeridianLink’s agentic architecture. - Partner with engineering leads to embed AI into each SDLC phase: requirements (AI-assisted grooming agents), development (co-pilot and Claude Code standards), testing (test-driven development metrics), and release (zero-downtime deployment, feature flag governance). - Establish and continuously improve team processes that increase quality and productivity through process definition, education, and refinement. - Facilitate lightweight agile ceremonies (planning, standups, retrospectives) and drive continuous improvement through retrospective assessments. - Use tools such as Jira (and related reporting) to support teams and enable visibility into progress, capacity, and delivery health. Bridge product and engineering AI alignment. Qualifications - 7+ years of technical program management in a software engineering organization, with at least 2 years in an AI, ML, or platform transformation context. - Demonstrated experience managing AI/ML initiatives or SDLC modernization programs — not just awareness, but delivery ownership. - Fluency with AI-driven SDLC concepts: AI-assisted requirements, co-pilot/code generation tooling, test automation, agentic deployment, and observability. - Ability to translate engineering complexity into executive narratives and vice versa; strong stakeholder management across CTO, VPs, and ICs. - Experience running programs that span multiple scrum teams, including offshore-heavy organizations. - Hands-on with program/project tooling (Jira, Confluence, or equivalents) and familiarity with engineering metrics (DORA, SPACE, or similar frameworks). What Success Looks Like (First 90 Days) - Delivery plans are clear, realistic, and transparent; stakeholders consistently know status, risks, and next steps. - Dependencies are surfaced early and managed actively; team execution rhythms are consistent and effective. - AI-related initiatives have strong delivery hygiene (milestones, measurable outcomes, and aligned execution across data/Product/Engineering). Why This Role You’ll play a pivotal role in delivering cross-functional technology initiatives—and help the organization execute confidently as AI becomes a more central part of products and operations. You’ll bring clarity, momentum, and structure to complex work while partnering with leaders across Engineering, Product, and Data.

• Own end-to-end project execution: plan, schedule, and drive delivery across the full project lifecycle, balancing constraints and keeping work moving forward in partnership with product and engineering counterparts. • Build and maintain project plans, track milestones, and proactively manage risks, issues, and tradeoffs—providing clear stakeholder updates with recommended solutions. • Serve as the PMO lead for the ML's agentic platform and customer facing products — the structured methodology for developing, testing, deploying, and operating AI agents within MeridianLink’s agentic architecture. • Partner with engineering leads to embed AI into each SDLC phase: requirements (AI-assisted grooming agents), development (co-pilot and Claude Code standards), testing (test-driven development metrics), and release (zero-downtime deployment, feature flag governance). • Establish and continuously improve team processes that increase quality and productivity through process definition, education, and refinement. • Facilitate light weight agile ceremonies (planning, standups, retrospectives) and drive continuous improvement through retrospective assessments. • Use tools such as Jira (and related reporting) to support teams and enable visibility into progress, capacity, and delivery health. Bridge product and engineering AI alignment.

• Own end-to-end product management for BigQuery Connectors, Looker dashboards, and AI Agents, from requirements through QA, documentation, and ongoing health monitoring • Define product specs and acceptance criteria in partnership with division leaders and SMEs • Monitor product health, usage metrics, and production incidents; address issues with urgency • Make recommendations on what to productize, sunset, maintain, or optimize • Own the sprint planning process end-to-end, in partnership with a Project Manager • Oversee data engineer hours and priorities across sprint cycles • Own backlog prioritization, capacity planning, and sprint completion accountability • Balance competing priorities across new development, maintenance, and custom client work • Execute the productization of validated R&D innovations in partnership with the Director of Engineering & Product • Enable Engineering to transform prototypes into production-ready products • Create maintenance plans and support models; partner with the Innovation team on handoff requirements • Own cross-functional relationships with R&D, division leads, Marketing, and AI Strategy • Serve as the primary point of contact for data product questions and timelines • Translate technical constraints and capacity realities into clear stakeholder communication • Manage data access and permissions across Looker and data platforms • Own platform integrations, system administration, and compliance with data security and client confidentiality requirements • Maintain monitoring dashboards for system health and usage • Manage Product Managers and conduct performance reviews and career development conversations • Build clear roles, responsibilities, and success criteria as the team scales • Develop product management capability in direct reports

Role Description The Product Owner supports translating business needs into functional software solutions. This individual works closely with Product Management and Engineering to help define and deliver product features that are valuable, usable, and feasible. The Associate Product Owner assists in understanding customer requirements and breaking them into actionable tasks while following a structured process within two-week iterations. This role helps maintain a healthy backlog and ensures the delivery of high-quality features aligned with business priorities. - Backlog Management: Own, define, and prioritize the product backlog, ensuring it is transparent, visible, and clearly articulated to the development team. - User Story Creation: Write clear, concise, and detailed user stories with acceptance criteria to guide the development process. - Sprint Planning and Execution: Actively participate in all Scrum events, including sprint planning, daily stand-ups, sprint reviews, and retrospectives, to ensure the team is focused on delivering the highest value. - Stakeholder Communication: Serve as the primary liaison between the development team and internal and external stakeholders, providing updates on progress, managing expectations, and gathering feedback. - Requirement Clarification: Be available to the development team to answer questions, clarify requirements, and make quick decisions to remove roadblocks. - Acceptance of Work: Review and accept completed work from the development team to ensure it meets the defined user story and acceptance criteria. - Feature Prioritization: Constantly evaluate and re-prioritize the product backlog based on business value, technical dependencies, and market feedback. Qualifications - Strong foundation in product ownership and telephony technology, typically gained through 4–5 years of experience in a B2B SaaS environment. - Experience in the automotive space is a plus, but not required. - Ability to work within Agile (Scrum) frameworks. - Experience managing and prioritizing product backlogs. - Ability to translate business needs into clear, well-written user stories. - Thoughtful, analytical approach to problem-solving with a keen eye for detail and quality. - Proactive, entrepreneurial self-starter who enjoys collaborating across teams and balancing multiple priorities. - Familiarity with tools like Jira, Azure DevOps, or Asana is helpful.