Senior Software Engineer, Workday
Context and Semantics (AI)
$190.1-285.1k
Enterprise AI platform for managing HR, finance & IT
Be an early applicant
Enterprise AI platform for managing HR, finance & IT
1001+ employees
Be an early applicant
$190.1-285.1k
1001+ employees
Company mission
To leverage the power of AI to elevate humans and supercharge work, moving business forever forward.
Role
Who you are
- 8+ years of professional software engineering experience focusing on backend architecture, data engineering, or distributed systems
- 5+ years of strong hands-on programming expertise in Java, Python, Scala, or Go
- 1+ years of dedicated experience building production-grade LLM applications, RAG pipelines, Vector Search systems, or Knowledge Graphs
- Bachelor’s degree (Master’s preferred) in Computer Science, Software Engineering, or equivalent technical field
- Experience building or optimizing distributed SQL query engines (e.g., Trino, Presto, Spark) and bridging operational and analytical data stores
- Deep understanding of modern AI orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel) and embedding models
- Proven ability to architect scalable, high-performance REST/gRPC APIs and microservices
- Experience handling sensitive, highly regulated data with a strong understanding of enterprise security boundaries and data governance
- Thrives in Ambiguity: A highly autonomous builder capable of taking open-ended AI product goals and breaking them down into concrete, scalable engineering realities
- Experience with the Workday platform or enterprise SaaS architectures is a strong plus
What the job involves
- As a Senior Software Development Engineer in Context and Semantics, you will be a lead builder and technical anchor for the infrastructure powering Workday’s AI Agents
- You will be hands-on in designing, coding, and scaling the backend systems that connect our foundational models to highly complex enterprise data
- Your day-to-day will sit at the intersection of distributed data engineering and applied AI
- You will build advanced RAG (Retrieval-Augmented Generation) pipelines, implement vector search infrastructure, and develop query federation layers (eg, Trino/LDQ) that seamlessly route LLM data requests across our transactional (OMS) and analytical (Data Lake) stores
- We are looking for a highly autonomous, product-minded engineer who thrives in ambiguity, writes exceptionally clean code, and is passionate about solving the unique latency, cost, and security constraints of enterprise AI
- System Design & Coding: Architect, build, and deploy robust backend services, APIs, and data pipelines that form the core semantic and context layer for Workday’s AI Agents
- AI & RAG Infrastructure: Design and optimize enterprise-grade RAG pipelines, including embedding generation, intelligent chunking strategies, and vector database integration (e.g., Pinecone, Milvus, Elasticsearch)
- Query Federation & Semantic Routing: Build and scale distributed query execution layers (leveraging technologies like Trino) to seamlessly fetch and translate context across transactional systems and data lakes
- LLM Orchestration: Develop dynamic context and memory management workflows using modern AI orchestration frameworks (e.g., LlamaIndex, LangChain, GraphRAG) to enable complex, multi-turn agentic reasoning
- Security & Guardrails: Embed rigorous data privacy, tenant isolation, and Role-Based Access Control (RBAC) directly into the retrieval and context layers to ensure governed AI execution
- Performance & Scale: Optimize system architectures for low-latency retrieval and high-throughput LLM interactions, tackling constraints around token management and context-window efficiency
- Technical Leadership: Mentor mid-level and junior engineers, lead code and design reviews, and establish engineering best practices for this new 0-to-1 product area
Our take
Workday is a cloud-based software vendor that provides management of workforces and finances. The company uses a single database for workforce management and financial management to offer integration and optimize business intelligence across companies. It has added to the packages and tools it offers over the years, providing analytic options that allow companies to combine third-party data with information collected by Workday.
The company has also grown through acquisitions and partnerships to broaden its capabilities. Most recently, in 2025 it purchases Sana, an AI-driven enterprise knowledge and learning platform, to create a "new front door for work". This acquisition allows Workday to integrate Sana's AI-powered search, agents, and learning capabilities with its own data and workflows, allowing employees to access information, automate tasks, and complete their day entirely within Workday.
Through a combination of strategic acquisitions and in-house development, Workday has built a comprehensive suite of HR, financial, and enterprise tools. By focusing on innovation and AI-driven workflows, the company continues to push productivity and decision-making for organizations worldwide. Building on this track record, Workday is very much positioned for even more growth, reinforcing its status as a leader in shaping the future of work.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
16% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Oct 2011
$85m
SERIES F
Apr 2009
$75m
SERIES E
Total funding: $215.3m
Company HQ
Pleasanton, CA
Leadership
Aneel Bhusri
(Co-Founder & CEO)Annel began their career at Morgan Stanley as a Corporate Finance Analyst. They then spent nearly 6 years at PeopleSoft as a Senior VP before co-founding Workday in 2005.
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