Software Engineer - Context and Semantics (AI)

Workday•Pleasanton, CA

2d•$123,900 - $222,000•Hybrid

About The Position

The Software Development Engineer in Context and Semantics will help develop the data and context infrastructure powering Workday’s AI Agents. Working with senior engineers and technical leads, the role builds clean, scalable backend software connecting large language models to complex enterprise data stores. The work includes implementing advanced retrieval-augmented generation (RAG) pipelines, integrating vector databases, and developing query federation services that route requests between transactional and analytical systems. The Context and Semantics Engineering team builds semantic layers, knowledge graphs, query federation engines, and dynamic context systems to ground generative AI in HR and Finance data. Its systems help Workday’s autonomous agents reason accurately, securely, and with contextual awareness at global scale.

Requirements

At least 3 years of professional software engineering experience focused on backend development, microservices, or data systems.
At least 2 years of hands-on programming experience in Java, Python, Scala, or Go.
At least 1 year of coursework, personal projects, or professional exposure to AI/ML concepts, LLM APIs, vector databases, or RAG architectures.
Bachelor’s degree in Computer Science, Software Engineering, or an equivalent technical field.
Solid foundation in data structures, algorithms, distributed systems concepts, and REST/gRPC API design.
Familiarity with SQL, relational databases, or distributed data processing engines such as Trino, Presto, or Spark.
Understanding of modern cloud infrastructure (AWS or GCP) and CI/CD development workflows.
Strong problem-solving skills, willingness to learn, and interest in emerging AI technologies.
Strong verbal and written communication skills and a collaborative, team-first mindset.

Nice To Haves

Master’s degree in Computer Science, Software Engineering, or an equivalent technical field.

Responsibilities

Design, develop, and test scalable backend microservices, APIs, and data pipelines for the context and semantic layer powering AI Agents.
Help build and maintain enterprise RAG pipelines, including embedding workflows, document chunking strategies, and vector database integrations.
Support development of distributed query execution features, using technologies such as Trino, to retrieve enterprise data securely for LLMs.
Implement orchestration logic and context-management components using AI frameworks such as LlamaIndex and LangChain for multi-turn agent interactions.
Ensure code adheres to enterprise requirements for data privacy, tenant isolation, and Role-Based Access Control (RBAC).
Write unit and integration tests, participate in code reviews, and help maintain system reliability, low latency, and operational monitoring.
Collaborate with Senior Engineers, Product Managers, and team leads to translate technical requirements into code deliverables.