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Latinx in AI (LXAI) · 2 weeks ago

Sr. Software Engineer (Agentic Workflow)

Boulder, CO

Full-time

Onsite

Senior Level

$176K/yr - $264K/yr

5+ years exp

Workday, Inc. is a Fortune 500 company and a leading AI platform for managing people, money, and agents. They are seeking a Senior Software Engineer to design and develop intelligent, agentic workflows that enhance financial planning processes for global enterprises.

Artificial Intelligence (AI)Big DataConsultingEducationMachine LearningProfessional Services

Responsibilities

Build Agentic Workflows: Design and develop sophisticated AI agents that reason, learn, and interact across complex business processes to enhance productivity and decision-making

Integrate AI Frameworks: Embed secure, scalable, and reliable agentic capabilities into core Adaptive Planning features—driving smart automation for FP&A users

Partner Cross-Functionally: Collaborate with extraordinary engineers and product managers to bring ideas to life—from concept to customer impact

Own Projects End-to-End: Lead the full AI development lifecycle—problem framing, data prep, model training, deployment, evaluation, and continuous improvement

Leverage Rich Planning Data: Harness Workday Adaptive Planning’s vast enterprise datasets to tune and optimize your AI models for high-value outcomes

Qualification

PythonMachine LearningDeep LearningJavaAI FrameworksCloud ComputingData EngineeringGenerative ModelsLarge Language ModelsContainerizationSoft Skills

Required

5+ years experience working on a data science, machine learning or related software development team

5+ years experience with Python and supporting numeric libraries, with experience in shipping production code and models

3+ years of experience object oriented programming in Java

2+ years experience in machine learning and deep learning frameworks & toolkits such as Pytorch and Sklearn

Bachelor's degree in a relevant field, such as Computer Science, Mathematics, or Engineering

Preferred

PhD or MS degree in a relevant field, such as Computer Science, Mathematics, or Engineering

Publications in machine learning research are highly desirable

Practical experience with generative models, large language models (LLM), retrieval augmented generation (RAG) systems, transformer neural networks

Experience with cloud computing platforms (e.g. AWS, GCP), containerization technologies (e.g. Docker) and data engineering pipelines (e.g. ETL)

Experience developing and deploying machine learning solutions using large-scale datasets, including specification design, data collection and labeling, model development, validation, deployment, and ongoing monitoring

An ability to balance speed with delivering high-quality, practical solutions

Shown perseverance in overcoming significant problems