Principal Software Development Engineer
Explicitly mentions vibe coding and related tools (MCP, langgraph) while building agentic LLM-based workflows.
About the Role
Lead the design and delivery of production-grade AI/ML systems for Workday Adaptive Planning, building agentic workflows and intelligent features that improve enterprise financial planning. Provide technical leadership across the ML lifecycle, mentor engineers, and integrate scalable, secure AI capabilities into core products.
Job Description
Role
As a Principal Software Development Engineer on the Workday Adaptive Planning team you will design and build production-grade, agentic AI/ML workflows that enhance financial planning at enterprise scale. You will lead technical design, deliver secure and scalable AI capabilities integrated into core products, and mentor engineering teams.
Key Responsibilities
- Lead design and development of sophisticated AI agents that reason, learn, and interact across complex business processes.
- Integrate secure, scalable, and reliable agentic capabilities into Adaptive Planning features.
- Own projects end-to-end: problem framing, data preparation, model design and development, deployment, evaluation, and continuous improvement.
- Leverage large-scale enterprise planning data to tune and optimize models for high-value outcomes.
- Provide technical mentorship, conduct code reviews, and unblock engineering teams.
- Partner cross-functionally with product managers and engineers to deliver customer-facing solutions.
Requirements
Basic Qualifications
- 4+ years experience on a data science, machine learning or related software development team.
- 4+ years experience with Python supporting ML/AI libraries and shipping production solutions.
- 4+ years experience in object-oriented programming with Java.
- 6+ years experience in SaaS software development.
Other Qualifications
- Bachelor’s degree in Computer Science, Mathematics, Engineering, or related field (MS/PhD highly desired).
- Extensive experience with large language models (LLMs), retrieval-augmented generation (RAG), semantic search, and text embedding models.
- Familiarity with vibe coding, MCP, langgraph, and transformer neural networks.
- Experience with cloud platforms (e.g., AWS, GCP), containerization (e.g., Docker), and data engineering pipelines (e.g., ETL).
- Strong focus on secure, high-quality software delivery, test automation, performance engineering, and model monitoring.
Work Model
Workday uses a flexible work approach: teams are expected to spend at least half (50%) of their time each quarter in the office or in the field. Remote “home office” roles exist with opportunities to convene in offices for key events.
Impact
Work impacts thousands of large enterprises and millions of end users by bringing AI-first capabilities to financial planning and FP&A workflows.