Job Details

Lead Cloud Machine Learning Engineer

Location: 100% Remote

Duration: 12 Month + Right to Hire

Client: Fortune 50 Healthcare Insurance Company

Team: AI Hub

Our client, a Fortune 50 healthcare insurance company, is seeking a Lead Cloud Machine Learning Engineer to spearhead the build-out of their AI Shared Services team. This fully remote, 12-month contract (with right to hire) role sits at the intersection of Cloud Engineering and Machine Learning, focusing on architecting and implementing enterprise-grade AI infrastructure and governance frameworks across cloud platforms such as AWS, GCP, and Azure. You will define the architecture, observability patterns, and security guardrails for centralized AI access, ensuring compliance, scalability, and cost efficiency. The successful candidate will design centralized AI model access solutions, enforce compliance and security guardrails, optimize cost and performance, and collaborate cross-functionally to ensure seamless integration and adherence to enterprise standards.

MINIMUM QUALIFICATIONS

• Deep experience with cloud platforms such as AWS, GCP, or Azure, including IAM, networking, security, and cost management
• Strong background in deploying and scaling machine learning and generative AI models in production environments
• Proficiency in Infrastructure as Code tools like Terraform, CloudFormation, or similar
• Familiarity with data platforms and governance tools such as Databricks, Delta Lake, and Unity Catalog
• Experience implementing security guardrails and compliance measures for PII and regulatory requirements in AI systems
• Demonstrated leadership skills in defining technical strategy and leading AI infrastructure build-out initiatives (no direct reports initially)

RESPONSIBILITIES

• Establish and architect foundational AI Shared Services on cloud platforms (AWS, GCP, Azure)
• Design and implement an AI Gateway (similar to Databricks Mosaic AI Gateway) to centralize AI model access, enforce governance, and enable:
  • Usage tracking and cost optimization
  • Automatic logging of inputs/outputs into Delta tables via Unity Catalog
  • Guardrails for PII protection and harmful content filtering
  • Rate limiting for performance and cost control
• Oversee secure access infrastructure for large language models (LLMs) and GenAI services in the cloud
• Define and implement observability, logging, and monitoring patterns to ensure compliance and operational excellence for AI workloads
• Collaborate with Data Science, Cloud Engineering, and Security teams to ensure seamless integration and compliance with enterprise standards
• Lead the technical strategy and roadmap for AI infrastructure, ensuring scalability, security, and cost efficiency