Senior Responsible AI Systems Engineer

Workday•Pleasanton, CA

2d•Hybrid

About The Position

This is an exciting opportunity to help build out both the operating model and technical systems that support a still-new but growing program at Workday: Responsible AI. As Workday accelerates both our development and use of AI internally, we must scale our ability to govern these systems through clear programs, repeatable processes, effective cross-functional execution, and practical automation. This is a systems engineering role at the intersection of engineering and governance, combining technical capability with strong cross-functional execution. The focus is on driving cross-functional Responsible AI initiatives from planning through implementation and adoption. The role combines strong program execution, technical fluency, operational judgment, and hands-on systems orientation. You will help coordinate and operationalize Responsible AI governance across Product, Engineering, Legal, Privacy, Security, Data, and other partner teams, while also contributing to the workflows, tooling, integrations, and automation that make that governance scalable. This role is well suited for someone who can move between program management and technical operations: organizing ambiguous work into actionable plans, aligning stakeholders, translating policy and governance requirements into system and process requirements, tracking risks and dependencies, and helping teams adopt new Responsible AI ways of working. You will work closely with the Lead Principal Responsible AI Systems Engineer to execute priority initiatives, support system implementation workstreams, and ensure Responsible AI workflows are delivered with quality, reliability, and appropriate technical rigor. This is a highly collaborative role. The Senior Responsible AI Systems Engineer will partner with product, ML engineering, data science, security, privacy, legal, and compliance teams to embed governance into the systems and processes where AI products and capabilities are built, deployed, monitored, and improved.

Requirements

Bachelor’s degree in quantitative science, Engineering, Information Systems, Business Administration, a related technical or operational field, or equivalent practical experience.
5+ years of experience with a Bachelor’s degree, or 3+ years with an advanced degree, in systems engineering, developer operations, product operations, technical program management, or a similar role developing or managing technical programs, tooling, systems, or automation.
3+ years of experience leading or coordinating complex, cross-functional technical initiatives from requirements through implementation, including working across engineering, product, legal, privacy, or other governance functions, and communicating status to senior stakeholders.
Experience translating business, legal, policy, risk, compliance, or governance requirements into operational processes, technical requirements, implementation plans, controls, or scalable workflows.
Experience working with technical systems, tools, platforms, workflows, automation, or integrations in partnership with engineering, product, data, privacy, security, legal, or compliance teams.

Nice To Haves

Familiarity with Responsible AI frameworks, policies, regulations, and standards, such as the NIST AI Risk Management Framework, EU AI Act, or similar governance frameworks is a strong plus.
Proficiency in at least one programming or scripting language (e.g., Python, Java) and experience with workflow orchestration or automation platforms a strong plus.
Technical fluency sufficient to partner effectively with engineering teams, understand system architecture and implementation tradeoffs, participate in troubleshooting, and help translate governance requirements into practical system or automation requirements.
Strong program management skills, including project planning, schedule development, status reporting, stakeholder management, risk mitigation, executive communication, and the ability to manage multiple concurrent deliverables.
Strong communication skills, with the ability to translate between technical and non-technical stakeholders and enable teams to adopt new systems, processes, and ways of working.
Comfort operating in highly ambiguous situations and building early-stage programs, processes, and systems in a still-maturing area.
Growth mindset, bias toward action, patience when needed, and a good sense of humor.

Responsibilities

Drive Responsible AI program execution across product and technical teams.
Lead and coordinate cross-functional Responsible AI initiatives from planning through delivery, including scope definition, requirements gathering, milestone tracking, risk management, stakeholder alignment, launch readiness, and post-launch adoption.
Translate Responsible AI requirements into scalable operating models.
Partner with Legal, Privacy, Product, Engineering, Security, and other stakeholders to translate policies, standards, regulatory requirements, and risk-management expectations into repeatable workflows, controls, playbooks, technical requirements, and implementation plans.
Work with the Lead Principal Responsible AI Systems Engineer to deliver priority systems and governance workstreams.
Work with the Lead Principal Responsible AI Systems Engineer on technical and programmatic priorities, helping break complex Responsible AI initiatives into executable workstreams, coordinating dependencies, and ensuring timely delivery across multiple partner teams.
Coordinate implementation of Responsible AI workflows and tooling.
Support the design, implementation, rollout, and continuous improvement of workflows, orchestration processes, automated checkpoints, evidence-capture mechanisms, dashboards, forms, and developer-facing interfaces that operationalize Responsible AI principles across the AI development and deployment lifecycle.
Partner on systems engineering and automation activities.
Contribute to the implementation, integration, testing, monitoring, maintenance, debugging, and improvement of Responsible AI tooling and platforms, working with technical leads and engineering partners to ensure systems are reliable, usable, scalable, and aligned with program requirements.
Operationalize evolving Responsible AI requirements.
Work with Responsible AI subject-matter experts and the Lead Principal Responsible AI Systems Engineer to translate emerging risks, regulations, standards, and use cases into updated controls, protocols, workflows, documentation, and technical implementation requirements.
Enable adoption by partner teams.
Create and maintain repeatable playbooks, process documentation, training materials, intake guidance, and self-service resources that help Product, Engineering, Product Legal, Global Legal Services, and other partner teams use Responsible AI systems and processes with decreasing reliance on bespoke support.
Improve processes through automation and operational rigor.
Identify opportunities to replace manual or bespoke processes with standardized workflows, reusable templates, automation, and system-driven controls; partner with technical teams to prioritize improvements that increase efficiency, consistency, observability, and scalability.
Support governance technology evaluation and continuous improvement.
Help evaluate workflow orchestration, automation, reporting, and integration capabilities needed to scale Responsible AI governance as Workday grows and regulatory requirements evolve.
Serve as a cross-functional Responsible AI implementation partner.
Represent the Responsible AI team in program, product, technical, and governance forums; communicate status and risks clearly; help stakeholders understand implementation expectations; and support adoption of Responsible AI-by-design practices across Workday.