Senior Agentic AI Architect/AI Solution Architect

Requirements

• 8–10 Years
• AWS AgentCore – Runtime, Memory, Gateway, Identity, Policy & Observability (Mandatory)
• AWS Bedrock and production-ready Agentic AI systems
• Context Engineering – Memory management, context optimization, prompt versioning & retrieval
• Harness Engineering – Tool orchestration, retries, validation & automated testing
• Python / FastAPI backend development
• Multi-Agent Orchestration using LangGraph / Strands Agents
• RAG pipelines, PostgreSQL, pgvector & enterprise knowledge integration
• MCP (Model Context Protocol) servers, clients & enterprise integrations
• AWS services: IAM, Secrets Manager, ECR, Aurora PostgreSQL, SQS, EventBridge & CloudWatch
• Docker, Kubernetes, Helm & Amazon EKS
• Next.js, TypeScript & full-stack application development
• AI security, enterprise SSO, Cedar/ABAC policies & human-in-the-loop workflows
• Agent observability, evaluation, monitoring & failure recovery
• Strong hands-on experience building and deploying production-grade agentic AI solutions.
• Expertise in context and harness engineering.
• Ability to own the complete AI solution lifecycle, from architecture and development to deployment and optimization.
• Experience building secure, scalable, and reliable enterprise AI automation workflows.

Schedule

• Onsite

How to apply

• Please share your updated resume by email.

Location

• Tampa, FL