Principal AI & Machine Learning Engineer
About The Position
Hewlett Packard Enterprise is seeking a Principal AI Engineer to lead the design, development, and deployment of AI/ML-powered applications. The role calls for strong hands-on application development experience, team leadership and mentoring, establishment of engineering best practices, and delivery of scalable, production-grade AI solutions aligned with business goals. The position is listed as onsite, with an expectation of primarily working from an HPE office, and requires onsite/hybrid work in Spring, Texas, or Sunnyvale, California. The engineer will develop AI applications, microservices, and APIs on Kubernetes infrastructure; build and maintain end-to-end AI pipelines; and work with business and technical partners to deliver secure, compliant solutions. The role also includes evaluating emerging AI technologies and maintaining technical documentation, deployment runbooks, and standard operating procedures. The role requires at least 12 years of hands-on software engineering experience, focused on AI/ML application development and deployment. A bachelor's or master's degree in Computer Science, Engineering, AI/ML, or a related field is required. The stated base salary range is $178,000–$361,000 annually in California or $157,000–$361,000 annually in Texas; variable incentives may also be offered. Actual offers may vary based on location, experience, education/training, and skill level.
Requirements
- 12+ years of hands-on software engineering experience, with a strong focus on AI/ML application development and deployment.
- Expertise in Kubernetes, including container orchestration, Helm charts, pod management, scaling, and troubleshooting.
- Strong experience with MLOps/AIOps tools and practices, such as MLflow, Kubeflow, Airflow, model registries, and monitoring frameworks.
- Hands-on experience with Azure, AWS, or GCP cloud platforms, including their AI services.
- Strong Python programming skills.
- Familiarity with FastAPI, Flask, or similar frameworks is mandatory.
- Hands-on experience with CI/CD pipelines and tools such as GitOps, Docker, Jenkins, or GitHub Actions.
- Ability to lead and mentor development teams, drive delivery, and manage technical priorities.
- Experience with Agentic and GenAI frameworks and vector databases.
- Experience with observability and monitoring tools such as Prometheus, Grafana, and OpenTelemetry for AI workloads.
- Good understanding of AI security, responsible AI principles, and governance frameworks.
- Bachelor's or master's degree in Computer Science, Engineering, AI/ML, or a related field.
Responsibilities
- Design, develop, and deploy AI applications, microservices, and APIs on Kubernetes-based infrastructure, ensuring scalability, reliability, and performance across development, staging, and production environments.
- Build and maintain end-to-end AI pipelines covering deployment, monitoring, versioning, and continuous improvement using modern MLOps/AIOps tools and practices.
- Lead and mentor a team of AI/ML engineers, conduct code reviews, and define best practices.
- Evaluate and adopt emerging AI tools, frameworks, LLM technologies, and open-source solutions to enhance platform capabilities and team productivity.
- Collaborate with Business Analysts, architects, and technical teams to align AI engineering with business objectives and ensure secure, compliant solutions.
- Establish and maintain technical documentation, deployment runbooks, and SOPs.
- Drive delivery and manage technical priorities.
Benefits
- Health and wellbeing benefits supporting physical, financial, and emotional wellbeing.
- Personal and professional development programs and career support.
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What This Job Offers
Job Type
Full-time
Career Level
Principal
