Role Overview
This role is responsible for designing, building, and governing secure, scalable, and compliant enterprise AI platforms on AWS, enabling AI/ML, Generative AI, LLMOps, Agentic AI, and MLOps capabilities while supporting application teams with platform adoption, deployment standards, security controls, and regulatory compliance in highly regulated environments.
Responsibilities
- Design and deliver secure, scalable, multi-tenant enterprise AI platforms on AWS.
- Build and enable Generative AI and LLMOps capabilities using Amazon Bedrock.
- Develop Agentic AI orchestration solutions using AWS Agent Core and integrated AWS services.
- Implement and manage production-grade MLOps platforms using SageMaker Pipelines, Model Monitor, and Feature Store.
- Establish AI platform standards, onboarding frameworks, and deployment best practices.
- Provide platform documentation and technical guidance to use case delivery teams.
- Ensure compliance with Responsible AI principles and regulations including HIPAA, GDPR, GxP, FDA, and EU AI Act.
- Define and enforce AWS security controls, governance, monitoring, auditability, and AI safety mechanisms.
Requirements
- 3+ years of Python development and platform engineering experience.
- 2+ years of hands-on AWS cloud engineering experience.
- 1+ years of experience in AI/ML, MLOps, data platforms, or Generative AI infrastructure.
- Strong expertise in AWS AI/ML services such as SageMaker, Bedrock, Agent Core, and related AWS services.
- Experience managing production environments with focus on security, reliability, scalability, governance, and cost optimization.
- Proficiency in Python and experience with AI orchestration frameworks such as LangChain, LlamaIndex, or DSPy.
- Good understanding of end-to-end AI solution architecture on AWS, including Bedrock Agents, knowledge bases, and prompt/model tuning.
- Strong knowledge of AI governance, regulatory compliance, and AWS security controls.
Skills
- Python
- AWS
- AI/ML
- Generative AI
- MLOps