Oracle Cloud Infrastructure (OCI) is developing scientific platform capabilities for genomics, pathogens research, and other computationally intensive scientific workflows. These capabilities help scientists execute workflows and connect scientific data, applications, and results. We are seeking a Senior Principal Product Manager to define product direction and deliver capabilities that address strategic customer needs while establishing a foundation for broader adoption.
This senior individual contributor role owns product strategy, customer discovery, roadmap, and product outcomes for scientific computing and genomics capabilities. You will work directly with scientists, research computing teams, engineering, and applied science to translate complex scientific workflows into reliable, usable cloud capabilities. You will operate independently across teams and guide product decisions from initial requirements through launch, adoption, and commercial validation.
Internal Responsibilities
Responsibilities
Define the product vision, strategy, roadmap, and investment recommendations for scientific computing and genomics within the broader product direction. Prioritize customer outcomes while identifying capabilities that can be reused across scientific programs and customers.
Build trusted relationships with scientists, bioinformaticians, research computing teams, and customer decision makers. Understand their scientific objectives, computational pipelines, data flows, existing tools, and operational constraints.
Translate customer discovery into clear requirements, user journeys, prioritized capabilities, release objectives, and acceptance criteria. Own product decisions throughout discovery, development, pilot deployment, launch, and continuous improvement.
Define the product experience for onboarding, configuring, executing, monitoring, and troubleshooting scientific computational workflows. Address identity, access, execution status, results, reproducibility, provenance, and cost visibility.
Partner with engineering and architecture on integration with established workflow engines, scientific applications, data systems, and cloud infrastructure. Make explicit tradeoffs across usability, performance, reliability, security, interoperability, cost, and delivery time.
Coordinate with the product owner for laboratory automation and robotics on workflows that span computational and physical experimentation. Define shared customer requirements for execution context, evidence, and continuity without duplicating capabilities owned by other systems.
Work with applied science and engineering to identify valuable artificial intelligence (AI) capabilities, scientific evaluation needs, and agent interactions. Define measures of correctness, reproducibility, user benefit, and appropriate human oversight.
Develop market and competitive insight, positioning, business cases, and adoption hypotheses. Partner with commercial teams on packaging, pricing recommendations, customer enablement, and the economics of expanding beyond initial engagements.
Establish and use measures for adoption, time to first successful workflow, onboarding effort, execution reliability, reproducibility, computational cost, and scientific workflow efficiency. Revise roadmap and investment recommendations using evidence.
Represent product direction to executives, customers, and partners. Resolve complex product issues across teams, mentor product colleagues, and establish effective discovery and decision practices through influence and technical credibility.
Minimum Qualifications
Bachelor’s degree in Computer Science, Engineering, Natural Sciences, Business, or a related discipline, or equivalent practical experience.
10+ years of relevant experience in product management, including substantial ownership of highly technical enterprise software, cloud, data, or platform products.
Demonstrated ability to independently lead product strategy and delivery across multiple teams, from ambiguous customer needs through launch and measurable adoption.
Experience working directly with technically sophisticated users and customers on scientific computing, data intensive workflows, AI platforms, or comparable complex technical environments.
Strong understanding of cloud infrastructure, distributed systems, application programming interfaces, data platforms, identity, and enterprise integration. Ability to evaluate scientific workflow and operational tradeoffs with engineers and architects.
Experience defining business cases, prioritizing investment, and using qualitative research and quantitative evidence to make product decisions. Excellent writing, executive communication, and influence across organizations.
Preferred Qualifications
Experience in genomics, bioinformatics, computational biology, pathogens research, scientific computing, or life sciences software, including direct engagement with researchers.
Familiarity with established scientific workflow engines, containerized execution, scientific interfaces, and reproducible computational environments.
Experience integrating research data, scientific applications, laboratory informatics, simulation tools, or computational workflows with cloud services.
Experience with AI enabled scientific applications, model evaluation, agents, and production cloud products, including commercialization and customer adoption.
External Responsibilities
Responsibilities
Define the product vision, strategy, roadmap, and investment recommendations for scientific computing and genomics within the broader product direction. Prioritize customer outcomes while identifying capabilities that can be reused across scientific programs and customers.
Build trusted relationships with scientists, bioinformaticians, research computing teams, and customer decision makers. Understand their scientific objectives, computational pipelines, data flows, existing tools, and operational constraints.
Translate customer discovery into clear requirements, user journeys, prioritized capabilities, release objectives, and acceptance criteria. Own product decisions throughout discovery, development, pilot deployment, launch, and continuous improvement.
Define the product experience for onboarding, configuring, executing, monitoring, and troubleshooting scientific computational workflows. Address identity, access, execution status, results, reproducibility, provenance, and cost visibility.
Partner with engineering and architecture on integration with established workflow engines, scientific applications, data systems, and cloud infrastructure. Make explicit tradeoffs across usability, performance, reliability, security, interoperability, cost, and delivery time.
Coordinate with the product owner for laboratory automation and robotics on workflows that span computational and physical experimentation. Define shared customer requirements for execution context, evidence, and continuity without duplicating capabilities owned by other systems.
Work with applied science and engineering to identify valuable artificial intelligence (AI) capabilities, scientific evaluation needs, and agent interactions. Define measures of correctness, reproducibility, user benefit, and appropriate human oversight.
Develop market and competitive insight, positioning, business cases, and adoption hypotheses. Partner with commercial teams on packaging, pricing recommendations, customer enablement, and the economics of expanding beyond initial engagements.
Establish and use measures for adoption, time to first successful workflow, onboarding effort, execution reliability, reproducibility, computational cost, and scientific workflow efficiency. Revise roadmap and investment recommendations using evidence.
Represent product direction to executives, customers, and partners. Resolve complex product issues across teams, mentor product colleagues, and establish effective discovery and decision practices through influence and technical credibility.
Minimum Qualifications
Bachelor’s degree in Computer Science, Engineering, Natural Sciences, Business, or a related discipline, or equivalent practical experience.
10+ years of relevant experience in product management, including substantial ownership of highly technical enterprise software, cloud, data, or platform products.
Demonstrated ability to independently lead product strategy and delivery across multiple teams, from ambiguous customer needs through launch and measurable adoption.
Experience working directly with technically sophisticated users and customers on scientific computing, data intensive workflows, AI platforms, or comparable complex technical environments.
Strong understanding of cloud infrastructure, distributed systems, application programming interfaces, data platforms, identity, and enterprise integration. Ability to evaluate scientific workflow and operational tradeoffs with engineers and architects.
Experience defining business cases, prioritizing investment, and using qualitative research and quantitative evidence to make product decisions. Excellent writing, executive communication, and influence across organizations.
Preferred Qualifications
Experience in genomics, bioinformatics, computational biology, pathogens research, scientific computing, or life sciences software, including direct engagement with researchers.
Familiarity with established scientific workflow engines, containerized execution, scientific interfaces, and reproducible computational environments.
Experience integrating research data, scientific applications, laboratory informatics, simulation tools, or computational workflows with cloud services.
Experience with AI enabled scientific applications, model evaluation, agents, and production cloud products, including commercialization and customer adoption.
