Value Engineering and Outcomes Engineer

At Roche you can show up as yourself embraced for the unique qualities you bring. Our culture encourages personal expression open dialogue and genuine connections where you are valued accepted and respected for who you are allowing you to thrive both personally and professionally. This is how we aim to prevent stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche where every voice matters.

The Position

Job description

As a member of the ACE Value Engineering & Outcomes (VEO) team you will play a key role in ensuring that AI and High Performance Computing (HPC) use cases are successfully translated deployed and executed across Roches AI Factory and HPC infrastructure.

Operating at the intersection of business domains RDT AI teams (such as Applied AI) and platform engineering you will contribute to owning the end-to-end flow from use case intent to real running workloads. You will ensure that workloads are technically executable scalable and aligned with platform capabilities enabling rapid time-to-value and sustainable adoption and ensuring alignment between business intent and platform execution.

You will also contribute to defining and continuously improving how use cases move from concept to execution across the AI Factory and HPC ecosystem helping to establish repeatable and scalable pathways for workload execution.

Description of the area

Hosting and Infrastructure (HI) provides mission-critical on-premise infrastructure cloud hosting connectivity and technology products that enable all functions at every Roche site to develop innovate connect and deliver compliant digital products across the Roche Enterprise.

The Value Streams - Accelerated Compute Engineering (ACE) Team is focused on driving both customer success and platform success by acting as a center of excellence and delivery for the High Performance Compute and AI Infrastructure supporting AI and HPC use cases across Roche. This team facilitates seamless onboarding and adoption for business vertical customers needing accelerated computehelping those infrastructure consumers with needs optimized for high availability seamless data transfer flexibility speed and the rapidly changing needs of AIhelping achieve rapid time-to-value.

Within Accelerated Compute Engineering (ACE) the Value Engineering & Outcomes (VEO) team plays a critical role in the AI Factory ecosystem by ensuring that AI and HPC use cases are translated into executable workloads and successfully realized on platform infrastructure. Acting as a bridge between business domain teams RDT AI teams (such as Applied AI) platform engineering and infrastructure the VEO team ensures that demand entering the AI Factory is structured governed and aligned with platform capabilities enabling effective onboarding execution and measurable outcomes.

Job Responsibilities

Use Case Structuring Challenge & Readiness

• Partner with business domain teams and RDT AI teams (such as Applied AI) to clarify structure and constructively challenge AI and HPC use cases

• Assess readiness dependencies and feasibility across data infrastructure and platform constraints

• Ensure use cases are technically viable and aligned with platform capabilities before execution

• Identify gaps early and guide teams toward executable pathways

Workload Translation Architecture & Platform Routing

• Translate use cases into executable workload designs including compute storage orchestration and data requirements

• Define how workloads are deployed across AI Factory HPC and hybrid environments

• Leverage experience with containerized and distributed systems (e.g. Kubernetes HPC schedulers) to ensure workloads are production-ready

• Develop reusable patterns to standardize workload deployment and scaling

Platform Onboarding & Execution

• Drive onboarding of workloads into platform environments ensuring all technical prerequisites are met

• Work closely with engineering and platform teams to ensure workloads are successfully deployed and running

• Troubleshoot and resolve issues across the full stack from infrastructure to application behavior

• Ensure workloads progress from onboarding to first successful execution

Governance Integration & Execution Pathways

• Embed governance compliance and prioritization frameworks into execution pathways ensuring use cases are not only approved but operationally viable

• Ensure governance decisions are reflected in how workloads are structured routed and executed

• Act as a bridge between governance intent and real-world platform execution

• Help ensure that governance is not only defined but consistently applied through real execution practices

Outcomes Performance & Scaling

• Ensure workloads progress to successful execution and measurable outcomes aligned with business needs

• Identify performance scaling and reliability challenges in real-world environments

• Establish feedback loops to inform platform architecture and process improvements

• Contribute to scaling patterns across multiple use cases and domains

Cross-Functional Leadership

• Connect and align business domain teams RDT AI teams (such as Applied AI) platform engineering and infrastructure teams to enable successful workload execution

• Influence decisions across organizational boundaries to ensure successful delivery

• Provide clarity on execution pathways risks and constraints

• Contribute to shaping how the AI Factory ecosystem operates end-to-end

Performance & Optimization

• Track and improve time-to-value from use case intake to first successful execution

• Identify cross-team bottlenecks and optimization opportunities across intake translation and execution

• Contribute to continuous improvement of workflows and operating models

Qualifications

Education / Experience

• Bachelors degree or advanced degree in Computer Science Engineering or a related discipline

• Strong experience in AI/ML platforms or HPC environments

• Hands-on experience with containerized workloads and orchestration (e.g. Kubernetes CaaS) and/or HPC scheduling environments

• Proven ability to take workloads from concept to running systems

• Comfortable working across infrastructure platform and application layers

• Experience collaborating with both technical teams and business/domain stakeholders

Technical Skills

• Understanding of AI/ML or HPC workload characteristics

• Experience with cloud and/or on-premise compute environments

• Familiarity with orchestration frameworks (Kubernetes Slurm etc.)

• Ability to diagnose and resolve issues in real runtime environments

• Ability to connect technical solutions to business outcomes and use case needs

• Strong systems thinking and problem-solving skills

Leadership Skills

• Ability to influence without authority across engineering AI and business stakeholders

• Strong ownership mindset driving work through to execution and outcomes

• Comfortable operating in ambiguity and shaping new ways of working

• Enterprise mindset with strong collaboration across organizational boundaries

• Bias toward action and solving real problems not just defining them

Who we are

A healthier future drives us to innovate. Together more than 100000 employees across the globe are dedicated to advance science ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities foster creativity and keep our ambitions high so we can deliver life-changing healthcare solutions that make a global impact.

Lets build a healthier future together.

Roche is an Equal Opportunity Employer.