Senior AI Engineer, Workday
Full-Stack, Agent Factory
CA$169-253k
More information about location
Enterprise AI platform for managing HR, finance & IT
Be an early applicant
Enterprise AI platform for managing HR, finance & IT
1001+ employees
Be an early applicant
CA$169-253k
More information about location
1001+ employees
Company mission
To leverage the power of AI to elevate humans and supercharge work, moving business forever forward.
Role
Who you are
- 10+ years of professional software development experience, including significant full-stack ownership from modern frontend through backend services
- 5+ years with backend web frameworks; Python frameworks such as FastAPI, Flask, or Django preferred
- 2+ years integrating large models (LLMs, foundation models) and modern AI APIs into production, user-facing products
- 1+ years designing and scaling AI orchestration architectures — multi-agent or tool-calling frameworks, routing layers, or advanced RAG pipelines
- 4+ years using cloud platforms (e.g., AWS, GCP) to deploy responsive, scalable systems
- Track record of shipping AI and agentic features that real customers use in production, and owning them after launch — prototypes alone aren't the bar
- Product-first mindset: you apply large models to solve practical user problems, not to showcase the technology
- Practical command of LLM constraints (token and cost management, context-window efficiency, caching, streaming, fallbacks) and of evaluation — rapid prototyping, benchmarking outputs, and automated metrics for retrieval quality and agentic behavior
- Strong understanding of the governance, guardrails, and security layers required when deploying autonomous agents over sensitive enterprise data
- Proven ability to architect the application layer around AI models: reusable patterns for predictability, error handling, and seamless UX integration
- Strong experience with React or a comparable framework, TypeScript, state management, and modern build tooling, plus a commitment to accessibility (WCAG 2.1/2.2)
- Deep knowledge of backend service architecture, microservice patterns, and REST API design, with proficiency in Python and ideally Kotlin or Java
- 5+ years with relational databases (PostgreSQL preferred) and non-relational stores, including query analysis and indexing optimization
- Strong grasp of distributed-system trade-offs, with the ability to independently diagnose and optimize performance at scale
- Hands-on with Infrastructure-as-Code, CI/CD automation, Docker and Kubernetes, observability, incident support, and secure coding practices
- A natural technical leader: people follow your direction because of your clarity and judgment, not your title. You measure success by what the team ships, not only by what you ship
- Proven track record leading engineering workstreams end to end and mentoring junior-to-mid-level engineers into stronger ones
- Confident presenter who is comfortable owning the room, and steady when a project is visible, ambiguous, or under real time pressure
- Collaborative and decisive: you seek input broadly, disagree and commit, and keep momentum without steamrolling
- Highly autonomous builder who turns open-ended product goals into concrete, scalable engineering plans
- Bachelor's degree (Master's preferred) in Computer Science, Software Engineering, or an equivalent technical field
- Experience integrating ML services or data pipelines into web applications; familiarity with Elasticsearch, rich-text editors or document-parsing tools, C4 diagramming, or Workday XO lifecycle management
What the job involves
- You'll own the end-to-end design, implementation, and product integration of our intelligent agents — and build the full-stack product surface those agents live in. Our ML Engineers build and optimize the foundational algorithms; your mission is intelligence orchestration and product delivery, connecting the brain to the product
- Expect to be hands-on across React frontends, backend microservices, APIs, data models, asynchronous workflows, agent orchestration layers, and delivery infrastructure. Because these agents work with sensitive HR and financial data at global scale, you'll help implement the guardrails that keep them private, predictable, and explainable
- This is the most senior engineering role on the team. You'll set the technical direction for our agent architecture, mentor the engineers around you, and be the person who presents the work when the stakes and visibility are highest
- Design and implement agentic workflows — orchestration and routing layers, tool calling, retrieval pipelines, memory, and multi-step reasoning — and integrate foundation models into customer-facing HR and Finance workflows
- Build and operate end-to-end features across React frontends, backend microservices, APIs, data models, and CI/CD. You build it, you run it
- Own the constraints that make agents viable in production: latency, cost per interaction, context-window efficiency, determinism, and graceful failure
- Build the evaluation loop — offline and online evals, benchmarking agent behavior against product requirements, and production observability of agent traces
- Implement Responsible AI in practice: guardrails, permission and data-boundary enforcement, PII handling, auditability, and explainability
- Lead high-visibility projects end to end and present them with confidence in design reviews, demos, and executive updates
- Make the call when the team needs one — gather input quickly, commit to a direction, document the trade-offs, and adjust as evidence arrives
- Mentor engineers, raise the technical bar, and partner closely with Product, UX, Machine Learning, and platform teams
Our take
Workday is a cloud-based software vendor that provides management of workforces and finances. The company uses a single database for workforce management and financial management to offer integration and optimize business intelligence across companies. It has added to the packages and tools it offers over the years, providing analytic options that allow companies to combine third-party data with information collected by Workday.
The company has also grown through acquisitions and partnerships to broaden its capabilities. Most recently, in 2025 it purchases Sana, an AI-driven enterprise knowledge and learning platform, to create a "new front door for work". This acquisition allows Workday to integrate Sana's AI-powered search, agents, and learning capabilities with its own data and workflows, allowing employees to access information, automate tasks, and complete their day entirely within Workday.
Through a combination of strategic acquisitions and in-house development, Workday has built a comprehensive suite of HR, financial, and enterprise tools. By focusing on innovation and AI-driven workflows, the company continues to push productivity and decision-making for organizations worldwide. Building on this track record, Workday is very much positioned for even more growth, reinforcing its status as a leader in shaping the future of work.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
16% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Oct 2011
$85m
SERIES F
Apr 2009
$75m
SERIES E
Total funding: $215.3m
Company HQ
Pleasanton, CA
Leadership
Aneel Bhusri
(Co-Founder & CEO)Annel began their career at Morgan Stanley as a Corporate Finance Analyst. They then spent nearly 6 years at PeopleSoft as a Senior VP before co-founding Workday in 2005.
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