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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Development Engineer - AI Tools - **Company:** Workday, Inc. - **Location:** Atlanta, GA, United States (Remote available) - **Experience:** Expert - **Salary:** $123,900.0 - $222,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Code Generation, Code Review, Information Leak Prevention, Programming Tools, Python (Programming Language), Key Management, Service-Oriented Architecture, Software Engineering, Systems Integration, TypeScript, Workflow Management Systems, AI Infrastructure, Datadog, Data Logging, Enterprise Software Applications, Cloud Platform System, ReactJS, Large Language Models, Prompt Engineering, Model Validation, Backend, Build Management, AI Platforms, Kubernetes, Restful APIs, Workday, Docker - **Published:** September 16, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=df3c59212db1c38d ## About the Role 5+ years of software engineering experience - 3+ years building and operating backend services or platform infrastructure in production - Strong proficiency in Python and/or TypeScript - Hands-on experience building or integrating with LLM APIs (OpenAI, Anthropic, etc.) and familiarity with prompt engineering, evaluation pipelines, and model selection tradeoffs - Robust understanding of AI security principles and responsible AI practices - including prompt injection, model misuse, data leakage risks, output validation, and operationalizing policy guardrails in production AI systems - Genuine excitement about being on the leading edge of AI - you follow new model releases, tooling shifts, and emerging frameworks closely, and you bring that energy into what the team builds Other Qualifications - Hands-on experience designing and building AI agents, including fluency with agentic frameworks and patterns such as ReAct - and practical experience shipping agents that are reliable in production - Experience building MCP servers, Claude skills, or similar tool-use integrations that extend AI capabilities to real workflows - Comfort designing REST APIs and service-oriented architectures - Experience with container orchestration (Kubernetes, Docker) and deploying services to cloud environments; experience with workflow orchestration tools and infrastructure-as-code is a plus - Understanding of enterprise security patterns: authentication, authorization, SSO, and secrets management - Exposure to observability tooling - logging, metrics, tracing - and a habit of building systems that are easy to monitor - Comfort partnering directly with the engineers who use your tools - you see user feedback, support channels, and adoption work as part of the job, not a distraction from it - Strong written and verbal communication skills; able to drive alignment across engineering, security, and product stakeholders ## Description 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 Welcome to the AI Tools team at Workday! We identify, deploy, and scale AI-powered tools that eliminate friction from the developer experience - and extend those capabilities to the broader organization as they mature. We build the AI platform layer that powers code generation, AI-assisted code review, agentic workflows, and enterprise-wide developer tooling. We own the MCP registry and gateway that connects Workday's developers to AI capabilities, and we build the technical guardrails that operationalize how AI is used responsibly across the company. If you want to do high-impact AI infrastructure work in enterprise software, we'd love to hear from you. About the Role The Workday AI Tools team is looking for a senior engineer who thrives at the intersection of AI, platform engineering, and developer experience. You'll design and build systems that thousands of Workday engineers rely on every day - from LLM gateways and MCP server infrastructure to AI-native agents and compliance tooling. You'll help define how we integrate emerging AI capabilities into our platform, and you'll be a technical anchor on a team that moves fast and takes quality seriously. You'll also work directly with the engineers using these tools - through office hours, Slack support, and our Champions program - and your work will be shaped by their feedback. In this role you will: - Design and build the AI platform layer: LLM gateways, MCP registries, abstraction APIs, and shared infrastructure that teams across Workday build on - Architect and implement AI agents and automation that improve the developer workflow - code review, documentation, testing, and beyond - Drive the evaluation and integration of AI model providers, keeping a strong eye on cost, safety, and performance tradeoffs - Serve as a scout for emerging AI capabilities - track new models, tools, and frameworks, and make recommendations to engineering leadership on when to adopt, evaluate, or pass - Lead technical design on complex, cross-cutting projects in partnership with Security, DevEx, and infrastructure teams - Build observability and governance tooling that gives the organization visibility into how AI tools are being used - Operationalize AI policy and compliance requirements into our platform