Senior AI Software Engineer (Deployment Technology)

Workday; Ireland; On-site; EUR 110,000 - 150,000; Full time

Job summary

Workday in Dublin is seeking an AI Software Engineer in Deployment Technology to design and build AI-powered systems that guide and automate complex Workday implementation tasks.

You will collaborate with PM, data science, and platform engineering to bring AI capabilities from concept to production, helping customers deploy faster and stay self-sufficient after go-live.

Qualifications

• Experience in Python and building AI-powered applications.
• Hands-on experience with Large Language Models and tool-use patterns.
• Experience deploying AI capabilities at scale on a cloud platform.

Responsibilities

• Design, build and deploy AI-powered features that automate complex deployment tasks.
• Integrate AI/ML models into Deployment Technology products from prototype to production.
• Collaborate with product, data science, and platform engineering to operationalize AI capabilities.
• Improve performance, reliability and cost-efficiency of AI systems.

Skills

Python

LLM integration

AI systems design

LangGraph

LangChain

LangSmith

Cloud platforms

Asynchronous systems

Cross-functional collaboration

Communication

Tools

AWS

GCP

Azure

LLM tooling

Python libraries

ML frameworks

Job description

• The Deployment Technology team is transforming how Workday is deployed and managed. Our mission is to reduce deployment time, cost and complexity while helping customers realize value faster


• We build products that help Workday implementation teams and partners get customers live faster by making it easier to discover proven setup approaches, reuse configuration, automate repetitive work and use AI-powered tools to guide and complete complex implementation tasks


• We also help customers become more self-sufficient after deployment, making it easier to manage and maintain Workday, adopt new products and features, and stay on top of ongoing change through intuitive, AI-enabled experiences


• Working closely with customers, partners and product teams across Workday, we’re shaping the next generation of deployment technology across the full customer lifecycle


• As an AI Software Engineer in Deployment Technology — a newly created profile on the team, based in Dublin — you will design and build the AI-powered systems and tooling that guide and automate complex Workday implementation tasks


• You’ll work closely with Product Management, data science, and platform engineering to take AI capabilities from concept to production, helping implementation teams and partners deploy Workday faster and helping customers stay self-sufficient long after go-live


• Design, build and deploy AI-powered features and tools that automate repetitive implementation work and guide complex configuration tasks


• Integrate AI/ML models (including LLM-based capabilities) into Deployment Technology products, from prototype through production


• Build and maintain the infrastructure, pipelines, and monitoring needed to run AI systems reliably at scale


• Collaborate with Product Management, implementation teams, partners, and enablement to understand real deployment challenges and translate them into AI-driven solutions


• Continuously improve performance, reliability, and cost-efficiency of deployed AI capabilities


• Help define engineering standards and best practices for AI development, since this is a new and growing discipline on the team

Expert level proficiency in PythonExperience in LangGraph, LangChain, and LangSmithDemonstrated, hands‑on experience building applications with Large Language ModelsProficiency in at least one other statically‑typed language such as Java, Scala, Rust, or C++8+ years of experience in software engineeringAbove all, you’re a builder who combines deep technical expertise with genuine curiosity about applied AI, and you’re excited to help define a brand‑new engineering discipline on a team shaping the future of enterprise deploymentExperience implementing agentic design patterns where an LLM uses tools to interact with its environmentExperience developing and deploying applications on a major cloud platform (AWS, GCP, or Azure)Experience architecting complex, event‑driven systems capable of handling asynchronous tasksProven success working within fast‑paced, agile environments and cross‑functional teamsStrong communication skills, with the ability to collaborate with both technical and non‑technical partnersComfortable working with ambiguity and translating complex problems into clear, thoughtful solutionsCommitted to fostering an inclusive, team‑oriented environment and contributing to a culture of continuous improvement