Java Developer with Agentic AI

CA-One Tech Cloud Inc.

Dallas, TX, United States

10 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Java (Programming Language) Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Architectural Patterns Automation of Tests Microsoft Azure Code Generation Code Review Continuous Integration Software Design Patterns Fault Tolerance

+25 more

Graph Database Python (Programming Language) Neo4j Software Tools Software Engineering SPARQL Systems Integration Google Cloud Spring Cloud Large Language Models Multi-Agent Systems Prompt Engineering Spring-boot State Machines Backend Event Driven Architecture Kubernetes Enterprise Integration Apache Kafka Virtual Agents Functional Programming Restful APIs Terraform Stream Processing Microservices

Job description

Enterprise Integration & Architecture: Design, build, and maintain production-ready microservices using Java and Spring Boot, with high-performance event-driven pipelines powered by Apache Kafka.
Agentic AI & Knowledge Architecture: Build multi-agent workflows and complex orchestration pipelines using Lang Graph and Python. Model domain expertise using Knowledge Graphs to ground AI outputs in structured enterprise data.
ADLC Transformation: Champion and operationalize AI-Driven Software Development Life Cycle (ADLC) frameworks to accelerate engineering throughput, maintain high code quality, and automate automated testing/deployment loops.
Hands-on AI Tooling: Daily hands-on development leveraging AI coding agents and including in any one of the LLMs - Claude, Devin, and Antigravity CLI to automate complex code bases and workflow automation.
CoE Enablement & Standards: Establish best practices, architecture patterns, and governance frameworks for integrating GenAI and Agentic systems with existing core backend services across the organization.

Requirements

Java & Spring Boot: Deep expertise in Java (12+ preferred), Spring Boot, Spring Cloud, RESTful APIs, and microservices design patterns.
Event-Driven Architecture: Strong hands-on experience with Apache Kafka (producers, consumers, stream processing, topic architecture, and fault tolerance).
Enterprise Delivery: Solid track record of deploying resilient, high-scale applications into production environments.

AI & Agentic Capabilities

Python Proficiency: Strong functional programming capability in Python for AI framework integration.
Agentic Frameworks: Hands-on experience building cognitive state machines or multi-agent systems using LangGraph (or similar orchestration frameworks like LangChain/AutoGPT).
Knowledge Graphs: Experience with graph databases (e.g., Neo4j, Amazon Neptune, NetworkX) or semantic tech (RDF, SPARQL, Cypher) to represent contextual enterprise knowledge.
Modern AI Engineering Tools: Deep hands-on experience using Claude (Claude 3.5 Sonnet / API workflows), Devin, or AntiGravity CLI for code generation, architectural refactoring, and automated development tasks.

Process & Frameworks

ADLC Exposure: Comprehensive understanding of AI-Driven Development Life Cycles moving beyond basic prompt engineering into automated task breakdown, AI-assisted code reviews, automated refactoring, and continuous integration.

Nice to Have

Experience with Vector Databases (Pinecone, Qdrant, Milvus) and hybrid search implementations (Graph + Vector / GraphRAG).
Exposure to cloud-native deployments (AWS, Azure, or Google Cloud Platform) using Kubernetes and Terraform.
Familiarity with evaluation frameworks for LLMs and agentic systems (e.g., Ragas, TruLens).