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