About the job
Come be a part of Red Hat's charge to democratize AI with open source! Red Hat's Global Engineering Team is looking for a Principal Software Engineer to join our newly formed AI Engineering organization. This role will be located within the AI Innovation team in Red Hat AI Engineering, which leads frontier AI research in Red Hat and drives innovation for Red Hat's AI Portfolio. The AI Innovation Team conducts customer- and science-driven research and productizes outcomes via open-source software. Our focus is on bridging the gap between cutting-edge research and production by productizing research papers (often featured in top AI conferences like NeurIPS, ICLR and ICML) onto the Red Hat AI platform. We operate as an open organization where contributions are valued and expected from all levels. You will serve as a technical bridge between AI algorithms and the Red Hat AI platform. This is not just an execution role; it is a technical leadership position where you will participate in the development and implementation of novel algorithms alongside the research community (internal and external).
Responsibilities
Contribute high-quality, maintainable code to open-source AI/ML projects and internal tooling.
Develop and optimize scalable toolkits for synthetic data generation, model training, and inference-time scaling.
Document system designs, API specifications, and model performance metrics to ensure transparency and reproducibility.
Evaluate existing product offerings and iterate on improvements based on telemetry metrics and direct user feedback.
Proficiently leverage AI-assisted development tools to accelerate coding, testing, and documentation workflows.
Serve as the Technical Lead for your assigned components, defining technical standards and providing architectural guidance to the wider team.
Influence the architectural direction of the Red Hat AI platform to ensure readiness for cutting-edge ML algorithms.
Work across multiple squads to align technical priorities, contribute to sprint planning, and translate high-level requirements into actionable engineering tasks.
Lead comprehensive code reviews and enforce best practices in testing (CI/CD), security, and maintainability.
Mentor and upskill junior engineers, fostering a culture of technical excellence and continuous learning.
Collaborate closely with Research Scientists and Product Managers to operationalize complex algorithms.
Qualifications
Minimum
Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
Must be able to work Hybrid in Boston
Proficiency in at least one modern backend programming language (e.g., Python, Go, Rust, Java) with a strong grasp of distributed systems patterns.
Solid experience designing and deploying microservices on containerized platforms (e.g., Kubernetes, OpenShift) at large scale.
Experience with large language models and model customization techniques.
Prior experience specifically building or optimizing developer tooling for ML/AI workflows (MLOps).
Demonstrated experience with rigorous testing methodologies, including unit, integration, and performance testing.
Proficiency in integrating AI tools into your daily development workflow to enhance productivity and efficiency.
Demonstrated interest in Artificial Intelligence/Machine Learning with a self-motivated drive to understand and navigate ambiguity in fast-paced, AI research-oriented environments.
Preferred
Advanced programming expertise in Python, specifically related to the ML ecosystem.
Proven track record of contributions to Open Source projects or communities.
Deep knowledge of machine learning frameworks (e.g., PyTorch, TensorFlow).
Advanced degree (Master’s or PhD) in Machine Learning, NLP, or a related field.
Experience with Red Hat products.