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# Onsite - AI Solution Architect - Generative AI, Agentic AI & Java - St. Louis, MO | New York, NY | Stamford, CT

- **Company:** ITBrainiac Inc
- **Location:** St. Louis, MO, United States
- **Experience:** Expert
- **Contract:** Contract
- **Skills:** LangGraph Framework, Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Cloud Computing, Cloud Computing Security, Software Design Patterns, Distributed Systems, Identity and Access Management, Machine Learning, Microsoft Message Queuing, OpenAI, Amazon Simple Notification Service (SNS), Software Engineering, Pinecone, Enterprise Software Applications, Spring Cloud, Large Language Models, Multi-Agent Systems, Prompt Engineering, Spring-boot, AgentCore, Generative AI, AWS Lambda, Amazon Virtual Private Cloud (VPC), Agentic-AI, Event Driven Architecture, Pgvector, Information Technology, Amazon Bedrock, Apache Kafka, Graphql, Machine Learning Operations, Claude, Api Design, Api Gateway, Model Context Protocol, Data Pipelines, OpenSearch, Microservices, Agent2Agent Protocol
- **Published:** October 14, 2026
- **Apply:** https://www.dice.com/job-detail/a3470018-1cc5-4303-9e59-4c8703b75019

## About the Role

This role requires an architecture-focused professional who can establish technical standards, lead end-to-end solution design, mentor senior engineers, and guide cross-functional teams in adopting AI-first architecture principles. Candidates must have practical implementation experience in at least one AI solution and a strong understanding of enterprise-scale AI integration., * 8-10 years of overall experience in software engineering and enterprise architecture.

 * Strong architecture-level expertise in Core Java, Java 21+, Spring Boot, and microservices.
 * Demonstrated hands-on experience implementing at least one AI-powered solution.
 * Enterprise-level experience with Generative AI, Agentic AI, and LLM integration.
 * Strong experience designing scalable, secure, cloud-native applications on AWS.
 * Proven ability to lead architecture decisions, mentor senior engineers, and guide cross-functional teams.
 * Excellent problem-solving, technical communication, and architectural decision-making skills.

Education

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

## Description

We are seeking an experienced AI Solution Architect with strong expertise in enterprise architecture, Java, Generative AI, and Agentic AI. The ideal candidate will have hands-on experience implementing AI-powered solutions and designing scalable, secure, cloud-native applications using AWS., * Design and architect enterprise-grade AI/ML-powered applications using Java and AWS cloud services.

 * Define architecture standards, design patterns, and best practices for integrating AI into Java-based ecosystems.
 * Lead end-to-end architecture for microservices, APIs, event-driven systems, and data pipelines supporting AI/ML model serving.
 * Design and implement Agentic AI and multi-agent solutions for enterprise environments.
 * Architect LLM-powered applications using AWS Bedrock, OpenAI, or Anthropic Claude.
 * Design Retrieval-Augmented Generation (RAG) solutions and integrate vector databases.
 * Conduct architecture reviews, threat modeling, security assessments, and performance benchmarking.
 * Optimize model inference, prompt engineering, prompt caching, and token consumption.
 * Mentor senior engineers and provide technical leadership to cross-functional teams.
 * Ensure scalability, reliability, security, and performance of enterprise AI applications.

Required Technical Skills

Java & Enterprise Architecture

 * Core Java, Java 21+
 * Spring Boot and Spring AI
 * Enterprise application architecture and design patterns
 * Microservices and distributed systems
 * Event-driven architecture using Kafka, AWS SQS, and SNS
 * REST and GraphQL API design
 * gRPC architecture and design

Generative AI & Agentic AI

 * Hands-on implementation of enterprise AI solutions
 * Agentic AI and multi-agent frameworks
 * Spring AI, LangGraph, Google ADK
 * Agent-to-Agent (A2A) protocols and Model Context Protocol (MCP)
 * LLM integration using Anthropic Claude, OpenAI, or AWS Bedrock
 * Retrieval-Augmented Generation (RAG) architectures
 * Vector databases such as OpenSearch, Pinecone, or pgvector
 * Prompt engineering, prompt caching, and token optimization
 * Model serving and inference optimization

AWS Cloud & Infrastructure

 * Amazon Bedrock and Bedrock AgentCore
 * EC2, ECS/EKS, AWS Lambda, and API Gateway
 * S3, RDS, and Aurora
 * IAM, KMS, and Secrets Manager
 * VPC networking and cloud security
 * Deployment and scaling of AI-powered cloud applications