Senior AI Agentic Architect - AWS Bedrock & Orchestration

Valiant Technologies LLC; Tallahassee (FL); Presencial; USD 180.000 - 240.000; Tempo integral

Resumo da vaga

Valiant Technologies LLC is seeking a hands-on Senior Agentic AI Architect in the United States to design, build, and deploy enterprise-grade AI assistants and automation solutions. You will own the full lifecycle from design through deployment, focusing on AWS AgentCore, Bedrock, context management, and secure, observable architectures.

You will lead multi-agent orchestration, develop RAG pipelines with PostgreSQL, and implement scalable backend services using Python/FastAPI and frontends with

Qualificações

• Deep experience designing and deploying enterprise-grade AI assistants.
• Hands-on with AWS AgentCore and AWS Bedrock in production.
• Proficient in context management, tool execution, and validation.

Responsabilidades

• Design and build agentic AI systems with reasoning and planning.
• Own full development lifecycle from design to deployment.
• Develop ingestion and retrieval pipelines for RAG with PostgreSQL and pgvector.
• Coordinate multi-agent orchestration and event-driven automation.
• Implement security, memory, and observability controls including SSO and ABAC.

Conhecimentos

AWS AgentCore

Context Engineering

Harness Engineering

Python development

Multi-agent orchestration

Agentic systems

Ferramentas

AWS Bedrock

IAM

Secrets Manager

ECR

Aurora PostgreSQL

SQS

EventBridge

CloudWatch

EKS

LangGraph

Strands Agents

FastAPI

Next.js

TypeScript

Descrição da vaga

Valiant Technologies LLC is seeking a hands-on Senior Agentic AI Architect in the United States to design, build, and deploy enterprise-grade AI assistants and automation solutions. You will own the full lifecycle from design through deployment, focusing on AWS AgentCore, Bedrock, context management, and secure, observable architectures.

You will lead multi-agent orchestration, develop RAG pipelines with PostgreSQL, and implement scalable backend services using Python/FastAPI and frontends with