Job Title: GenAI /Bedrock Architect Location: Remote Duration: / Term: FTE Experience Desired: 15+ Years Job Description:

Key Responsibilities

Design, deploy, and manage enterprise Generative AI platforms using Amazon Bedrock. Configure and manage foundation models, model access, inference profiles, and API integrations. Build and operationalize RAG pipelines using Bedrock Knowledge Bases, Amazon OpenSearch, and vector databases. Implement and manage Bedrock Agents, AgentCore, Guardrails, and model evaluation frameworks. Develop reusable GenAI platform components, APIs, SDKs, and integration frameworks. Implement secure multi-account and multi-tenant AI platform architectures. Automate infrastructure provisioning and deployments using Terraform, CloudFormation, and CI/CD pipelines. Implement AI security and governance, including IAM, KMS, VPC endpoints, data protection, and model access controls. Establish monitoring, logging, token usage tracking, cost optimization, and performance management. Support production deployments, troubleshooting, scalability, and platform reliability. Required Skills AWS Bedrock: Foundation models, Knowledge Bases, Agents, AgentCore, Guardrails, inference APIs. Programming: Python, Boto3, REST APIs, AWS SDKs. GenAI Frameworks: LangChain, LangGraph, Strands Agents, or similar frameworks. RAG & Vector Databases: Amazon OpenSearch, pgvector, vector embeddings, semantic search. AWS Services: Lambda, API Gateway, S3, IAM, KMS, CloudWatch, Step Functions, ECS/EKS. Infrastructure as Code: Terraform or AWS CDK. DevOps: CI/CD, GitHub Actions, Jenkins, or AWS CodePipeline. Security: IAM policies, encryption, network isolation, guardrails, and enterprise AI governance. Observability: Model latency, token consumption, inference costs, tracing, and application monitoring. Key Skills: AWS, Agentic AI architecture, Bedrock, Migration, RAG.