Senior Core Java AI Architect

Openkyber; Alaska; Hybrid; USD 170,000 - 260,000; Full time

Job summary

Openkyber is seeking a Senior Core Java AI Architect in Saint Louis, MO with hybrid work. You will design and build enterprise-grade AI-enabled microservices using Java 21+, Spring Boot, and sophisticated LLM integrations.

Expertise in event-driven architectures, REST/GraphQL APIs, and gRPC is required to deliver scalable AI/ML solutions. You will work with cutting-edge tools like OpenAI, Anthropic Claude API, AWS Bedrock, and vector databases (OpenSearch, Pinecone, pgvector) to optimize model

Qualifications

• Experience with Agentic AI / multi-agent frameworks at enterprise scale.
• LLM integration via Claude API, OpenAI, or AWS Bedrock RAG architectures.
• Vector databases (OpenSearch, Pinecone, pgvector)
• Model serving, inference optimization, prompt engineering.
• Spring AI, Langgraph, Google ADK, A2A, MCP.
• Prompt Engineering, prompt caching, token optimization.
• AWS

Responsibilities

• Design and implement AI-enabled core Java microservices for enterprise AI workloads.
• Integrate LLMs and multi-agent agents across scalable architectures.
• Develop and optimize data pipelines for vector databases and model serving.
• Collaborate with teams on API design (REST/GraphQL) and event-driven patterns.
• Evaluate and implement AI/ML deployment best practices on AWS Bedrock / Anthropic/OpenAI.

Skills

Java 21+

Spring Boot

Spring AI Microservices

Event-driven

Kafka

SQS/SNS

REST API design

GraphQL API design

gRPC

Enterprise architecture

AI/ML integration

Tools

OpenAI

Anthropic Claude API

AWS Bedrock

OpenSearch

Pinecone

pgvector

Langgraph

Google ADK

A2A

Job description

Role: Senior Core Java AI Architect

Work Location: Saint Louis, MO 63131 Hybrid

Mandatory Skills: Java 21+, Spring Boot, Spring AI Microservices, event-driven architecture (Kafka, SQS/SNS) REST/GraphQL API design, gRPC Design patterns, Enterprise architecture and scaling AI / ML Integration

Description: Experience with Agentic AI / multi-agent frameworks at enterprise scale. LLM integration via Anthropic Claude API, OpenAI, or AWS Bedrock RAG architectures, vector databases (OpenSearch, Pinecone, pgvector) Model serving, inference optimization, prompt engineering Spring AI, Langgraph, Google ADK, A2A, MCP. Prompt Engineering, prompt caching, Token optimization. AWS