Senior AI Engineer - Sana

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.

You'll build the core agent infrastructure that powers Sana's mission to bring superintelligence to work. This is a greenfield opportunity to define how AI agents plan, reason, and execute across enterprise environments—building systems that reliably handle real-world complexity at scale. You'll work at the intersection of agent architecture, context-, tool- and prompt engineering, and production infrastructure.
 

In this role, you will

• Architect multi-step planning, orchestration, and tool routing for agents

• Implement code generation agents and sandboxed code execution

• Engineer memory, state, and context packing/grounding strategies

• Balance latency, quality, and cost controls for agent execution

• Develop safe fallbacks, graceful degradation and robust error handling

• Collaborate with platform and search teams to deliver reusable agent infrastructure

• Establish safety guarantees and measurable quality improvements

#SanaJobs

• 3+ years of software engineering experience building production backend or platform systems.

• 3+ years of experience in TypeScript, with a strong track record of writing reliable, maintainable services.

• 3+ years of experience with distributed systems, APIs, asynchronous workflows, and service-oriented architecture.

• 3+ years of experience designing systems with a focus on scalability, reliability, observability, and maintainability.

• Experience building and deploying LLM-powered applications in production.

• Experience building agent platforms or AI infrastructure.

• Deep understanding of the low-level details of the OpenAI, Google, and Anthropic LLM APIs, including tool calling, system prompt caching, etc.

• Familiarity with LLM application patterns, including tool calling, retrieval-augmented generation (RAG), memory and context management, multi-step orchestration, and human-in-the-loop systems.

• Experience building and running machine learning systems in production, including compiling training and test datasets, building training pipelines, evaluating models, and detecting and handling drift (neural networks, Gaussian models, Thompson sampling, etc.).

• Experience designing evaluation frameworks for LLM or agent quality and safety, including hands-on use of platforms such as Langfuse or LangSmith.

• Familiarity with vector databases, prompt and context engineering, and experimentation tooling.

• Experience working with sandbox environments such as Modal, and designing strict access control models to keep user data safe and encrypted at all times.

• Experience running services in Kubernetes-based environments on GCP or equivalent cloud platforms.

• Comfort working with Postgres and Redis in high-throughput, low-latency service contexts.

• Contributions to open source TypeScript projects.

• Ability to navigate ambiguity, make strong technical tradeoffs, and drive projects from concept to production.

• Strong communication and collaboration skills, with the ability to partner effectively across engineering, product, and AI research teams.

Listed below is the base salary range applicable to this position. Workday pay ranges (and the precise pay offered to the successful candidate) are based on a number of objective criteria such as relevant experience and skills, and educational qualifications, level of responsibility, demands of the role, work location and business need. 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 awarded by Workday Inc. For more information regarding Workday’s comprehensive benefits, please click here.

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