Description
We are looking for an experienced Principal AI Engineer to drive the design, development, and deployment of AI/ML-powered applications. The successful candidate will have strong hands-on experience in application development, lead and mentor a team of AI developers, define best practices, and deliver scalable, production-grade AI solutions aligned with business goals.
Key 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.
- Continuously evaluate and adopt emerging AI tools, frameworks, LLM technologies, and open-source solutions to enhance platform capabilities and team productivity.
- Collaborate closely with Business Analysts, Architects, and technical teams to align AI engineering efforts with business objectives and ensure secure, compliant solutions.
- Establish and maintain technical documentation, deployment runbooks, and SOPs.
Required Qualifications:
- 12+ years of hands-on experience in software engineering, with a strong focus on AI/ML application development and deployment.
- Expertise in Kubernetes – container orchestration, Helm charts, pod management, scaling, and troubleshooting.
- Strong 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.
- Experience working with Agentic and GenAI frameworks and vector databases etc.
- Experience with observability and monitoring tools (Prometheus, Grafana, OpenTelemetry) for AI workloads.
- Good understanding of AI security, responsible AI principles, and governance frameworks.
Benefits:
- Comprehensive suite of benefits supporting physical, financial, and emotional wellbeing.
- Investment in career development with programs to help reach career goals.
- Unconditional inclusion with flexibility to manage work and personal needs.
Salary:
- The expected salary/wage range for this position is $157,000 - $361,000 per year in Texas and $178,000 - $361,000 per year in California.