Principal Software Development Engineer for Machine Learning

About the Role

Key Responsibilities

• Own the architectural design and implementation of sophisticated AI systems and agentic AI capabilities, focusing on patterns such as tool calling, supervisor agents, multi-agent architectures, and human-in-the-loop integration.
• Ensure solutions are highly scalable, performant, and resilient in production environments, defining technical roadmaps and standard methodologies for ML system development and MLOps.
• Architect, implement, and deploy secure, RESTful web services in Python and Kubernetes, designing robust, multi-tenant runtime architectures for fast inference and scaling to millions of users.
• Lead the development and deployment of Python and Spark-based data pipelines for large-scale datasets, focusing on efficiency, reliability, and data quality.
• Provide technical leadership and guidance to fellow engineers, fostering a culture of engineering excellence, and participating in design reviews and code quality initiatives.
• Collaborate multi-functionally to translate requirements into technical designs and take ownership of high-quality solutions.
• Apply and advance industry-standard software engineering practices, including automation, observability, scalability, and MLOps, to deliver maintainable and testable code.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related technical field.
• 8 or more years of experience in production-level Software Development.
• 4 or more years of experience in Python, with a track record of shipping production code and systems.
• 4 or more years of experience building scalable data pipelines and working with large-scale datasets.
• 4 or more years of experience deploying production services to cloud platforms (e.g., AWS, Azure, GCP) and using containerization technologies (e.g., Docker, Kubernetes) for MLOps.
• Deep technical expertise in the engineering, deployment, and MLOps of advanced machine learning solutions such as generative models, LLMs, RAG, and AI agents.
• Strong understanding of scalable distributed systems, performance optimization, database technologies (e.g., PostgreSQL, Redis), and robust API development.
• Proven algorithmic thinking and experience designing, implementing, and analyzing efficient algorithms for complex problems.
• Ability to build flexible, reusable, and well-documented software components, with experience in code testing strategies (unit, integration, end-to-end) in a continuous deployment environment.
• Excellent communication and collaboration skills.

Nice to Have

• MS/PhD degree in Computer Science or Engineering.
• Experience with generative models, LLMs, RAG, and AI agents.
• Experience with cloud deployment and MLOps best practices.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 8+ years of professional software development experience.
• 4+ years of experience in Python and building scalable data pipelines.
• 4+ years of experience deploying services to cloud platforms and using containerization technologies.

Benefits & Perks

• Annualized base salary range: $179,200 USD - $268,800 USD (Colorado) or $170,200 USD - $302,400 USD (other US locations).
• Potential eligibility for Workday Bonus Plan, role-specific commission/bonus, and annual stock grants.
• Flexible work approach combining in-person and remote work, with at least 50% in-office or in-field time each quarter.
• Comprehensive benefits package (details available during hiring).