Senior Principal AI Engineer: Lead ML Systems & MLOps

Hewlett Packard Enterprise Development LP

Spring, Northern (TX, KY)

Hybrid

USD 152,000 - 349,000

Full time

12 days ago

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Job summary

Hewlett Packard Enterprise Development LP seeks an experienced Senior Principal AI & Machine Learning Engineer to design, develop, and deploy AI/ML-enabled applications. You will lead a team of AI engineers, define best practices, and deliver scalable AI solutions aligned with business goals.

Ideal candidates will have hands-on experience with Kubernetes, MLOps frameworks, cloud AI services, and strong Python skills (FastAPI/Flask).

Qualifications

12+ years hands-on experience in software engineering with a strong focus on AI/ML application development and deployment.
Kubernetes – container orchestration, Helm charts, pod management, scaling, and troubleshooting.
Experience with MLOps/AIOps tools and practices (e.g., MLflow, Kubeflow, Airflow, model registries, monitoring frameworks).
Hands-on experience with cloud platforms – Azure, AWS, or GCP, including their AI services.
Strong programming skills in Python; 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.
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 (Prometheus, Grafana, OpenTelemetry).
Good understanding of AI security, responsible AI principles, and governance frameworks.

Responsibilities

Design, develop, and deploy AI applications, microservices, and APIs on Kubernetes-based infrastructure.
Build and maintain end-to-end AI pipelines covering deployment, monitoring, versioning, and continuous improvement using MLOps/AIOps tools.
Lead and mentor a team of AI/ML engineers, conduct code reviews, and define best practices.
Continuously evaluate and adopt emerging AI tools, frameworks, LLM technologies, and open-source solutions.
Collaborate with Business Analysts, Architect and technical teams to align AI engineering with business objectives and ensure secure solutions.
Establish and maintain technical documentation, deployment runbooks and SOPs.