Design and operationalize enterprise-scale agentic AI platforms on AWS
Build and manage LLMOps frameworks, including: Prompt/version management, Model orchestration, Evaluation pipelines, Monitoring and observability
Develop and deploy LLM-powered applications using: Amazon Bedrock, Bedrock AgentCore, SageMaker
Implement scalable RAG architectures and vector search solutions
Integrate vector databases such as: OpenSearch, Aurora, PostgreSQL with pgvector, Pinecone or similar platforms
Design AI guardrails, governance controls, and responsible AI frameworks
Build workflow automation using: AWS Lambda, Step Functions, EventBridge
Establish secure, scalable, enterprise-grade infrastructure aligned with AWS best practices
Integrate AI platforms with APIs, enterprise systems, analytical platforms, and downstream applications
Collaborate with architects, product teams, engineering teams, and business stakeholders to drive AI innovation initiatives
Mentor engineering teams on AI platform standards and best practices

10+ years of software engineering, cloud engineering, or AI platform experience
5+ years designing enterprise AI/ML platforms in AWS environments
Hands-on experience with: Amazon Bedrock, Bedrock AgentCore, SageMaker, Agentic AI workflows
Strong experience designing and implementing Retrieval-Augmented Generation (RAG), Vector database architectures, LLMOps frameworks
Experience with: Prompt orchestration, Model evaluation, AI monitoring frameworks
Strong knowledge of: AWS infrastructure, IAM/security policies, Networking, Observability
Experience building scalable cloud-native applications and microservices
Strong Python development experience
Ability to translate business requirements into scalable AI platform solutions
Excellent communication and stakeholder engagement skills.

Principal AI Platform Engineer

Key skills