Description

Lead the design and implementation of secure, scalable, enterprise-grade AI and cloud solutions for healthcare research and data modernization.

This role is remote.

Responsibilities

• Design enterprise-scale AWS cloud architectures supporting AI/ML and Generative AI workloads, including microservices, containers, APIs, and serverless computing.
• Architect and integrate Generative AI platforms, LLM orchestration, AI agents, RAG pipelines, vector databases, and knowledge graphs.
• Implement AI governance frameworks covering responsible AI, guardrails, model monitoring, risk management, and compliance controls.
• Build secure enterprise MLOps pipelines for model training, validation, deployment, observability, and lifecycle management.
• Collaborate with DevSecOps to implement CI/CD pipelines, infrastructure as code (Terraform/CloudFormation), and security automation.

Required Skills

• 10+ years of experience in enterprise architecture, cloud engineering, or solution architecture.
• 5+ years of hands-on AWS cloud architecture experience.
• Deep expertise in Generative AI, Large Language Models (LLMs), and AI orchestration frameworks.
• Strong experience with MLOps, distributed systems, and cloud-native platform design.
• Proficiency in API architecture, event-driven systems, Kubernetes, and Docker.
• Hands-on experience with Infrastructure as Code using Terraform and CloudFormation.
• Strong DevSecOps and CI/CD implementation experience.
• Understanding of security architecture, governance, and compliance in enterprise cloud environments.

Preferred Skills

• AWS Certified Solutions Architect – Professional or AWS AI/ML Specialty Certification.
• Experience with LangChain, Bedrock Agents, and enterprise AI governance initiatives.
• Background supporting healthcare, research, nonprofit, or federal organizations.

Key Skills

Education

Any Graduate