Senior AI Engineer Sana

Your work days are brighter here.

Were 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 were shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join youll 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. Were 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 youre building smarter solutions supporting customers or creating a space where everyone belongs youll do meaningful work with Workmates whove got your return well 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 youve found a match in Workday and we hope to be a match for you too.

About the Team

About the Role

Youll build the core agent infrastructure that powers Sanas mission to bring superintelligence to work. This is a greenfield opportunity to define how AI agents plan reason and execute across enterprise environmentsbuilding systems that reliably handle real-world complexity at scale. Youll 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

About You

Basic Qualifications:

• 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.

Other Qualifications:

• 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.

Workday Pay Transparency Statement (For EU Locations Only)

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 Workdays comprehensive benefits please click here.

Our Approach to Flexible Work

With Flex Work were 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 youll 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.

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