Senior AI Engineer

Posted Yesterday
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Pleasanton, CA, USA
In-Office
176K-312K Annually
Senior level
Cloud • Fintech • HR Tech
The Role
Designs, builds, and integrates production-grade AI agents into Workday’s enterprise platform. Responsibilities include orchestrating LLM workflows, developing scalable backend architectures, implementing responsible AI guardrails, optimizing latency and cost, evaluating model performance, and integrating AI capabilities into user-facing products. The role also provides technical leadership, mentors engineers, and ensures privacy, reliability, predictability, and explainability for systems handling sensitive HR and financial data.
Summary Generated by Built In

Your work days are brighter here.

We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too.

About the Team

Agent Factory is where Workday’s next chapter gets built. We’re forming small, senior, cross-functional AI teams that bring together product leaders, AI engineers, and full-stack builders to create intelligent agents used by millions of people every day. This is production-grade AI—deeply embedded into Workday’s platform—not research experiments or maintenance work. Teams own problems end to end, collaborate tightly across disciplines, and use the right tools to solve real customer challenges at global scale. You’ll work at the intersection of AI, platform architecture, and human workflows, with the autonomy to shape how agents reason, act, and scale responsibly. High trust, high expectations, and real impact. Engineering, but brighter.

About the Role

As a Senior AI Engineer in Agent Factory, you will drive the end-to-end system design, implementation, and product integration for a core domain of Workday’s next generation of intelligent agents. While our ML Engineers focus on building, training, and optimizing foundational algorithms, your mission is intelligence orchestration and product delivery—connecting the brain to the product.

Sitting at the intersection of AI capabilities, enterprise platforms, and human workflows, you will develop and integrate foundational models safely and reliably into functional, production-grade software. You will be hands-on in the design, experimentation, and orchestration of complex agentic workflows, translating cutting-edge AI capabilities into scalable business value. Because these agents interact with sensitive HR and financial data at a global scale, you will be a key contributor to Responsible and Governed AI—implementing strict guardrails for data privacy, predictability, and explainability within your pod. This role requires a balance of domain-level system architecture and rigorous execution, solving critical product constraints like latency, cost, and reliability.

About You

About You

Basic Qualifications

  • 8+ years of professional software engineering experience with strong expertise in backend architecture, distributed systems, and API design, plus 1+ years of dedicated focus building production-grade LLM/agentic systems OR 5+ years of experience specifically within Machine Learning Engineering or AI application development, with 2+ years dedicated to shipping LLM-backed products.
  • 2+ years of hands-on experience integrating large models (LLMs, Foundation Models) and modern AI APIs into user-facing enterprise products.
  • 1+ years of experience designing and scaling AI orchestration architectures—including multi-agent frameworks, routing layers, or advanced RAG pipelines.
  • 4+ years of experience optimizing application performance (specifically tackling constraints like API latency and user interaction design), with 1+ years applied to modern LLM constraints (such as token management, cost optimization, and context-window efficiency).
  • 4+ years of proven experience leveraging cloud computing platforms (e.g., AWS, GCP) to deploy highly responsive, scalable systems.

Other Qualifications

  • Bachelor’s degree (Master’s preferred) in Computer Science, Software Engineering, or equivalent technical field.
  • Responsible AI Implementation: Strong understanding of how to execute governance, guardrails, security layers, and evaluation mechanisms necessary when deploying autonomous agents over sensitive enterprise HR and financial data.
  • Technical Leadership & Mentorship: Proven track record of technically leading engineering workstreams within a pod, taking ownership of the development lifecycle, and mentoring junior-to-mid level engineers.
  • Product-First AI Mindset: Deep focus on business value, user experience, and applying deep learning/large models directly to solve practical end-user challenges.
  • System Design & Reusability: Proven ability to architect robust application layers that wrap around AI models, establishing reusable patterns for system predictability, error handling, and seamless UX integration.
  • Experimentation & Evaluation: Skilled in rapid prototyping, benchmarking model outputs against product requirements, and setting up automated evaluation metrics (e.g., assessing retrieval quality and agentic behavior).
  • Thrives in Ambiguity: Highly autonomous builder capable of taking open-ended product goals and breaking them down into concrete, scalable engineering realities.


Workday Pay Transparency Statement

The annualized base salary ranges for the primary location and any additional locations are listed below.  Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday’s comprehensive benefits, please click here.

Primary Location: USA.CA.Pleasanton

Primary Location Base Pay Range: $208,000 USD - $312,000 USD

Additional US Location(s) Base Pay Range: $176,000 USD - $312,000 USD


Our Approach to Flexible Work
 

With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.

Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.

Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.


Workday is committed to providing reasonable accommodations for qualified individuals during our application process, in order to perform one or more essential functions of their job, as well as regarding the use of AI tools for employment decision-making to any degree. Please see below for more details including how to request an accommodation as a qualified veteran, due to a disability or for religious reasons, or as otherwise provided under applicable law.


Workday prohibits taking adverse action against any candidate or employee for reporting a possible violation of this policy, requesting one or more work accommodations, exercising a privacy right, or cooperating in an investigation in accordance with applicable law. Any employee who retaliates against a candidate or employee for doing so may be subject to disciplinary action, up to and including termination of employment, to the fullest extent allowable under applicable law.


If you require a reasonable accommodation, you may email [email protected], as far in advance as possible.


Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!

At Workday, we value our candidates’ privacy and data security.  Workday will never ask candidates to apply to jobs through websites that are not Workday Careers. 

  

Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not.

  

In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.

Skills Required

  • 8+ years of professional software engineering experience with strong expertise in backend architecture, distributed systems, and API design, plus 1+ year building production-grade LLM or agentic systems
  • Alternatively, 5+ years of experience in Machine Learning Engineering or AI application development, with 2+ years shipping LLM-backed products
  • 2+ years of hands-on experience integrating large models, foundation models, and modern AI APIs into user-facing enterprise products
  • 1+ year of experience designing and scaling AI orchestration architectures, including multi-agent frameworks, routing layers, or advanced RAG pipelines
  • 4+ years of experience optimizing application performance, including API latency and user interaction design, with 1+ year addressing LLM constraints such as token management, cost optimization, and context-window efficiency
  • 4+ years of experience leveraging cloud computing platforms such as AWS or GCP to deploy responsive, scalable systems
  • Bachelor's degree in Computer Science, Software Engineering, or an equivalent technical field
  • Master's degree in Computer Science, Software Engineering, or an equivalent technical field
  • Strong understanding of responsible AI governance, guardrails, security layers, and evaluation mechanisms for autonomous agents handling sensitive enterprise data
  • Proven technical leadership of engineering workstreams, ownership of development lifecycles, and mentorship of junior-to-mid-level engineers
  • Deep focus on business value, user experience, and applying deep learning or large models to practical end-user challenges
  • Ability to architect robust application layers around AI models with reusable patterns for predictability, error handling, and seamless user experience integration
  • Experience with rapid prototyping, model-output benchmarking, and automated evaluation metrics for retrieval quality and agent behavior
  • Ability to work autonomously in ambiguous environments and translate open-ended product goals into scalable engineering solutions

Workday Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Workday and has not been reviewed or approved by Workday.

  • Healthcare Strength — Health coverage is positioned as broad and well-supported, with multiple medical carrier options, virtual care access, and some locations offering onsite clinic/pharmacy services. Mental health support is described as notably strong, including therapy sessions and confidential support availability for household members.
  • Parental & Family Support — Family-related benefits are portrayed as extensive, including paid bonding and caregiver leave alongside fertility, adoption, and surrogacy reimbursement. Added support like parenting resources, milk-shipping/lactation assistance during travel, and backup child/elder care is explicitly outlined.
  • Strong & Reliable Incentives — Equity participation and savings-oriented programs are presented as meaningful components of total rewards, including an ESPP discount with a lookback feature. Additional programs like a student-loan pathway to earn the 401(k) match are included as financial-support enhancements.

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The Company
HQ: Pleasanton, CA
14,894 Employees
Year Founded: 2005

What We Do

Workday is a leading provider of enterprise cloud applications for finance, HR, and planning. Founded in 2005, Workday delivers financial management, human capital management, and analytics applications designed for the world’s largest companies, educational institutions, and government agencies. Organizations ranging from medium-sized businesses to Fortune 50 enterprises have selected Workday.

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