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

ITBrainiac IncStamford, CT🇺🇸United StatesPosted Oct 13, 2026

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Stamford, CT, United States
Posted
Yesterday
MicroservicesSpringSpring BootAPI GatewayAWSGenerative AIGraphQLJavaKafkaLLMRESTgRPC

Job Description

AI Solution Architect – Generative AI, Agentic AI & Java

Location: St. Louis, MO | New York, NY | Stamford, CT
Work Arrangement: Onsite from Day One
Duration: 12 Months
Experience: 8–10 Years
Interview Mode: Virtual Interview

 

Job Summary

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.

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.

 

Key Responsibilities

  • 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

 

Required Qualifications

  • 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.

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