Senior Developer, Agentic Ai Engineering

The Customer Agentic Solutions team is part of the Globalization Platform org, which develops and evolves Workday's internationalization and localization platforms while building out new agentic AI capabilities. Our ambition is to provide a fit-for-purpose language experience to our customers by partnering with internal teams through innovative and emerging technology capabilities.

Our team is specifically focused on providing Workday Agentic teams, App Devs and Customers with best-in-class AI-powered translation self-help services and solutions, thus globalizing Workday AI Agents and Customer Solutions. We create AI-powered software and self-help guidance (playbooks) for Workday App Devs, ensure the health of customer-facing services, continuously watch the AI domain for advancements, and improve engineering productivity by leveraging multi-agent software development tools.

Our engineering teams are passionate about automation and leveraging cutting edge AI technologies to drive innovation, leading to a brighter Workday for all. We value trust, transparency, value-driven innovation, continuous learning, collaboration, effective communication and accountability. Our team fosters brave, happy, innovative collaboration across continents and time zones, with deep mutual respect and a focus on building the right thing at the right time.

• As an SDE, you will be a full-stack product engineer who ships, operates, and continuously improves AI-powered features end-to-end. You will own problem framing, data contracts, model/tool selection, prompts, evaluations, safety, cost/latency optimization, and lifecycle governance for customer-facing AI services.
• You will play a key part in designing and developing AI-powered translation self-help services and solutions that globalize Workday AI Agents and Customer Solutions. Your focus will be on production reliability and business outcomes (adoption, quality, cost) at software-engineering speed, not research-heavy development.
• You will lead by example, demonstrating architecture and development best practices, while mentoring and empowering your fellow team members to achieve success. You are a problem solver and innovator who can work both independently and collaborating closely with teammates, PMs, Architects, and Linguists.

• Problem-Solving & Analytical Skills: You're not just a "coder." You can analyze business requirements, design robust AI-powered solutions, and troubleshoot complex AI systems and data flows. You understand the trade-offs between different AI approaches and can make pragmatic decisions.
• Communication & Collaboration: The role requires excellent communication skills. You must be skilled at gathering requirements from non-technical stakeholders (PMs, Linguists, Product Teams), explaining AI concepts clearly, and collaborating effectively with cross-functional teams.
• Business Context Understanding: You understand the "WHY" behind AI solutions. You can connect technical AI capabilities to business outcomes (adoption, quality, cost) and work with stakeholders to frame problems effectively.

• 7+ years software development experience with a focus on production systems and business outcomes.
• Expert proficiency in Python with strong emphasis on production-quality code and modern Python patterns. Deep experience with agentic AI frameworks like LangGraph (or LangChain), Pydantic for data modeling, asyncio for asynchronous programming, and observability tools like LangSmith. Proficiency with data manipulation libraries (pandas, NumPy), cloud SDKs (boto3), HTTP clients (requests, httpx). Experience with modern Python package managers like uv or poetry. Experience with Python testing frameworks (pytest), pre-commit hooks, and code quality tools (black, isort, flake8). Experience with production development practices, GitHub, CI/CD.
• Expert proficiency designing and developing solutions using Object Oriented (OO) languages like Java, C# or similar.
• Deep understanding of REST APIs, Graph APIs, and data formats like JSON and XML.
• Hands-on experience delivering products to market which combine traditional software engineering and AI capabilities, with emphasis on production reliability and operational excellence.
• Experience with end-to-end ownership of AI-powered features, including problem framing, model/tool selection, prompt engineering, evaluation frameworks, and lifecycle governance.

• Bachelor's degree in a relevant field, such as Computer Science, Mathematics, or Engineering.
• Agentic AI & Workflows: Practical experience with agentic AI systems, agentic workflows, and multi-agent architectures. Familiarity with frameworks like LangGraph, AgentForge, or similar.
• AI/ML Fundamentals: Strong understanding of neural networks, large language models (LLM), retrieval augmented generation (RAG) systems, transformer architectures, and generative models.
• Protocols & Integration: Experience with AI protocols such as Model Context Protocol (MCP), Agent-to-Agent (A2A), or similar integration patterns for AI systems.
• Service Orchestration: Experience with no-code/low-code orchestration platforms such as Flowise, n8n, PowerAutomate, Zapier, or similar workflow automation tools.
• Development Tools: Experience with AI-enhanced development environments and multi-agent SDLC tools (e.g., Cursor, Claude, GitHub Copilot) for improving engineering productivity.
• Prompt & Context Engineering: Practical experience with prompt engineering for developers and context engineering techniques for building effective AI systems.
  Cloud & Infrastructure: Experience with cloud computing platforms (e.g. AWS, GCP), containerization technologies (e.g. Docker), and data engineering pipelines (e.g. ETL).
• Customer-Facing Services: Experience building and operating customer-facing AI services with focus on reliability, cost optimization, and business metrics (adoption, quality, cost).
• Globalization/Translation: Experience or interest in internationalization, localization, or translation technologies is a plus.