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Xebia · 1 month ago

Technical Product Manager with Life science or Pharma Domain, R&D Platforms, GCP and AI experience

United States

Full-time

Remote

Senior Level, Lead/Staff

8+ years exp

Xebia is a global digital consulting company that has been delivering cutting-edge technology and consulting for over 20 years. They are seeking a Technical Product Manager with expertise in Life Sciences or Pharma Domain to lead product strategy and development for R&D platforms, focusing on continuous innovation and stakeholder engagement.

AnalyticsBig DataCloud ComputingConsultingDevOpsGenerative AIInformation TechnologyRobotic Process Automation (RPA)Software

H1B Sponsor Likely

Hiring Manager

Abhiuday Singh

Responsibilities

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

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

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

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

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

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

Qualification

GCPAI experienceLife sciences domain knowledgeProduct managementTechnical architectureAPIsAgile methodologiesJiraConfluenceStakeholder managementUser interview capabilitiesData engineering stackMLOps practicesConflict resolutionDocumentation skills

Required

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

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

Preferred

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

Background in managing external vendor relationships and integration points

Experience with multi-vendor coordination and dependency management

Understanding of security and compliance requirements in enterprise pharmaceutical environments

Knowledge of scientific data provenance, reproducibility, and regulatory requirements

Familiarity with life sciences software vendors (Schrödinger, Benchling, etc.)

Company

Xebia

Glassdoor3.6

Xebia is specialist op het gebied van Agile, Test Automation, Continuous Delivery, Architecture en Modern Software Development

Founded in 2001

Hilversum, Noord-Holland, NLD

5001-10000 employees

https://www.xebia.com

H1B Sponsorship

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