Senior Technical Product Manager

Role Description We are seeking a Senior Technical Product Manager to join our life sciences R&D product team supporting a leading pharmaceutical company's digital transformation initiatives. This role requires deep technical expertise combined with strategic product thinking to manage complex platform products that serve researchers, scientists, and data engineers across chemistry, biology, and computational science domains. As a Senior Technical Product Manager, you will own large strategic products OR manage portfolios of 5-10 established applications, driving continuous discovery, innovation, and business value delivery. You'll work in a hybrid delivery model aligned to the client's Product Development Lifecycle (PDLC), combining waterfall-style governance with agile execution. This is a partnership-driven role requiring close collaboration with client Program Managers, engineering teams, business stakeholders, and multi-vendor partners to deliver R&D acceleration—not just sustainment. What You'll Do Strategic Product Leadership Own end-to-end product strategy, roadmap definition, and business value validation for assigned R&D platform products Drive continuous discovery and innovation focused on new product development and R&D acceleration Lead product through all four PDLC governance checkpoints: Strategy Alignment → Requirements Validation → Architecture/Design Review → Launch Manage large strategic initiatives OR portfolios of 5-10 established applications (including modernization, rationalization, or sunsetting) Conduct continuous validation of business value through metrics, user feedback, and experimentation Product Requirements & Delivery Translate complex, ambiguous scientific and technical requirements into clear Product Development Plans (PDPs) Create comprehensive user stories with clear acceptance criteria and robust requirements traceability Manage backlog prioritization using Jira, Confluence, and Jira Product Discovery Partner with Project Managers on scope trade-offs, resource allocation, and dependency management Drive UAT, release decisions, and launch readiness across technical and business stakeholders Stakeholder Management & Discovery Serve as primary point of contact for business stakeholders and R&D end-users Map stakeholder landscapes (influence, needs, communication frequency) and develop tailored engagement strategies Conduct user interviews, discovery sessions, and continuous feedback loops with researchers and scientists Facilitate requirements validation workshops and design reviews Present executive-ready materials to business leadership and governance forums Technical Platform Expertise Deep understanding of APIs, data flows, cloud platforms (GCP required), and R&D systems architecture Work closely with engineering, infrastructure, and data platform teams on technical feasibility and design Monitor support channels, triage technical requests, and align them with product strategy Understand GCP services (BigQuery, Workflows, Vertex AI, Cloud Run, GCS) and integration patterns Navigate complex data ecosystems, authentication systems (SSO, LDAP), and compliance requirements AI-Native Product Management Leverage Gemini Pro and Atlassian AI for intelligent prioritization, velocity forecasting, and automated insights Apply NLP-based sentiment analysis and predictive analytics to inform backlog prioritization Co-develop AI use cases with client teams (target: 2-3 production AI use cases per quarter) Drive GenAI-powered documentation generation and requirements automation Governance & Reporting Participate actively in bi-weekly sprint planning, retrospectives, and delivery reviews Attend monthly Product Strategy Reviews with business stakeholders and Product Owners Contribute to quarterly 360° performance reviews and monthly portfolio health reporting Maintain comprehensive Confluence documentation and knowledge management practices Qualifications 8+ years of product management experience, preferably in technical or platform products Strong business use case analysis and user interview capabilities Proven stakeholder mapping, management, and conflict resolution abilities Excellent requirements documentation and PRD writing skills Deep understanding of agile development methodologies and hybrid delivery models Expert user of Jira and Confluence for backlog management and documentation Requirements Strong technical background with hands-on software engineering or technical architecture experience Deep understanding of cloud platforms, with GCP experience required Experience building or managing developer platforms, APIs, data pipelines, and infrastructure tooling Ability to read technical documentation, understand data flows, and speak fluently with engineers and data scientists Working knowledge of modern data engineering stack and databases (SQL, NoSQL) Familiarity with MLOps practices and AI/ML platform requirements Experience in pharmaceutical or regulated industry environments (GxP, 21 CFR Part 11) Understanding of scientific research workflows and R&D systems Ability to bridge the gap between scientific users (chemists, biologists, computational scientists) and engineering teams Familiarity with scientific computing applications and high-performance computing (HPC) environments Recommended Qualifications Experience with high-performance computing (HPC) environments and HPC-to-cloud migrations Knowledge of GCP's HPC-specific offerings and configurations Understanding of authentication systems (SSO, LDAP) and zero-downtime deployment strategies Familiarity with data movement challenges specific to large scientific datasets Certification in relevant cloud technologies (GCP Professional Cloud Architect, etc.) Strong strategic vision for product direction and long-term roadmaps Experience as a product evangelist with ability to drive adoption and change management Track record of portfolio rationalization, modernization, and technical debt reduction Capability in cost optimization: license utilization, cloud spend efficiency, ROI analysis Background in AI/GenAI applications for scientific workflows Key Performance Indicators (KPIs) You will be evaluated quarterly through 360° reviews and objective business metrics: 360° Review Criteria User/Stakeholder Management: Proactive engagement, conflict resolution, strategic alignment Requirements Creation & Completeness: Clear, testable user stories; robust Product Development Plans Understanding of Assigned Products: Deep domain knowledge; strategic roadmap ownership Jira Maintenance/Upkeep: Backlog hygiene, documentation quality, requirement traceability Objective Business Metrics Cycle time reduction for research workflows and product delivery User satisfaction (NPS) and adoption rate improvements for managed applications Cost optimization: Portfolio rationalization savings, license utilization, cloud spend efficiency Innovation velocity: AI/automation use cases co-developed per quarter