Senior Principal Software Engineer

Introduction

At IBM Finance & Operations, we are the backbone of IBM’s transformation driving efficiency, transparency, and smart decision-making across the business. Our teams provide the insight and discipline that guide strategy, ensure financial strength, and enable IBM to invest in innovation and growth. Working in Finance & Operations means combining analytical skills with collaboration and curiosity. You’ll partner with colleagues across functions and geographies, using data, technology, and process excellence to create solutions that improve performance and deliver measurable impact. IBM offers continuous learning, career development, and a culture that values diverse perspectives. Join us and be part of a global team that keeps IBM moving forward, while building your own future in a dynamic and evolving environment.

Your Role And Responsibilities

The Data And AI team is a highly focused effort to lead digital-first execution and transformation at Red Hat leveraging data & AI strategically for our customers, partners, and associates. The engineering team is focused on building and delivering strategic AI Factory platform for building Skills and Agents, designed to augment human capabilities, accelerate business workflows, and scale operations across the enterprise.

In this role, you'll take ownership of end-to-end AI/ML systems, champion best practices, and deliver impactful, production-grade models. You’ll work autonomously, mentor others, and collaborate with data, engineering, and product teams to bring AI features into production.

What you will do?

• Design, build, and evolve ML pipelines that cover data ingestion, preprocessing, feature engineering, training, validation, deployment, and monitoring.
• Design, build, and evolve MCP server, Skills and Agents that enable and empower Red Hatters to do business efficiently.
• Translate research prototypes and models into production-quality code, ensuring robustness, scalability, and maintainability.
• Select appropriate algorithms and modeling techniques, perform hyperparameter tuning, and conduct comparative experimentation.
• Evaluate and validate model performance using advanced metrics (e.g. ROC-AUC, precision/recall curves, calibration, fairness, drift) and set up continuous validation/regression checks.
• Collaborate with software engineers, data engineers, and SRE/DevOps to integrate ML services into broader systems.
• Instrument models and systems with monitoring, logging, alerting, and automated healing or scaling mechanisms.
• Troubleshoot and resolve production incidents, root-cause errors, data drifts, performance regressions, or infrastructure issues.
• Mentor more junior engineers, lead code reviews, and help establish ML lifecycle and quality standards.
• Stay current with emerging ML research, frameworks, and tooling, and proactively propose improvements or experiments.
  
  

Preferred Education

Bachelor's Degree

Required Technical And Professional Expertise

• Bachelor's degree in Computer Science, Computer Engineering, or related field.
• 5 years of software development experience with a focus on machine learning pipelines or machine learning applications or building ML platforms
• Exceptional software engineering skills that lead to elegant and maintainable data platform
• Proficiency in at least one general purpose programming language, eg. Python, Go, Java, Rust, etc.
• Loosely held strong opinions and perspectives that you kindly debate, defend, or change to ensure that the entire team moves as one
• Sets and resets the bar on all things quality, from code through to data, and everything in between
• Deep empathy for your users of your platform, leading to a constant focus on removing friction, increasing adoption, and delivering business results
• Prunes and prioritizes work in order to maximize your contributions and impact
• Bias for action and leading by example
• Past experience in building enterprise data platforms that have a high level of governance and compliance requirements
  
  

Preferred Technical And Professional Experience

• Familiarity with open source or inner source development and processes
• Familiarity of data mesh architectural principles
• Experience with Snowflake, Fivetran, dbt, Airflow / Astronomer
• Deep hands on knowledge of Vector Databases, RAG Pipelines is a huge plus.
  
  

Personal qualities and communication

• Communication skills and experience in interacting with cross functional business and engineering teams
• Capability in undertaking business needs analysis in direct consultation
• Motivated with a passion for quality, learning and contributing to collective goals
• Excellent communication, presentation, and writing skills