Job Title: Senior Java Developer AI/LLM Solutions
Location: Dallas, TX (Onsite)
About the Role
We are seeking an experienced Senior Java Backend Developer with hands-on expertise in building scalable backend applications and integrating AI-powered solutions, Large Language Models (LLMs), and Generative AI technologies. The ideal candidate will have a strong foundation in Java microservices development while leveraging modern AI frameworks such as LangChain, LangGraph, OpenAI APIs, Azure OpenAI, or AWS Bedrock to build intelligent enterprise applications.
This role involves designing, developing, and deploying highly scalable APIs and backend services that power AI-driven business solutions.
Key Responsibilities
Backend Development
- Design, develop, and maintain enterprise-grade backend applications using Java 17/21.
- Develop scalable RESTful APIs and Microservices using Spring Boot and Spring Cloud.
- Build highly available distributed systems following microservices architecture.
- Implement asynchronous processing using Kafka, RabbitMQ, or JMS.
- Optimize application performance, scalability, and reliability.
- Develop secure APIs using OAuth2, JWT, Spring Security, and API Gateway.
AI & LLM Integration
- Integrate applications with Large Language Models (LLMs) such as:
- OpenAI GPT
- Azure OpenAI
- Anthropic Claude
- Google Gemini
- AWS Bedrock
- Llama Models
- Develop AI-powered backend services for:
- Intelligent search
- Chatbots
- AI Assistants
- Document Processing
- Knowledge Management
- Code Generation
- Summarization
- Recommendation Engines
- Implement Retrieval Augmented Generation (RAG) architectures.
- Build prompt orchestration and prompt engineering pipelines.
- Integrate vector databases for semantic search.
- Develop AI agents using modern multi-agent frameworks.
- Monitor AI model performance and optimize prompts for accuracy and cost.
AI Frameworks
Hands-on experience with one or more:
- LangChain
- LangGraph
- Spring AI
- Semantic Kernel
- LlamaIndex
- CrewAI
- AutoGen (preferred)
Backend Architecture
- Design event-driven architectures.
- Build high-performance APIs.
- Develop resilient distributed systems.
- Implement caching using Redis.
- Build scalable workflow engines.
- Integrate third-party enterprise APIs.
Database Development
Experience with:
Relational Databases
NoSQL Databases
Vector Databases
- Pinecone
- ChromaDB
- Weaviate
- Milvus
- PGVector
Cloud & DevOps
Develop and deploy applications using:
Cloud Platforms
- AWS
- Azure
- Google Cloud Platform
Services
- Kubernetes
- Docker
- OpenShift
- ECS/EKS
- Azure Kubernetes Service
CI/CD
- Jenkins
- GitHub Actions
- GitLab CI
- Azure DevOps
Infrastructure
Observability
Experience with:
- Prometheus
- Grafana
- Datadog
- ELK Stack
- Splunk
- OpenTelemetry
Required Technical Skills
Core Java
- Java 17/21
- Spring Boot
- Spring MVC
- Spring Data JPA
- Spring Security
- Spring Cloud
- Hibernate
- Maven/Gradle
API Development
- REST APIs
- GraphQL (preferred)
- OpenAPI/Swagger
- gRPC (nice to have)
Messaging
- Apache Kafka
- RabbitMQ
- ActiveMQ
AI Technologies
- Prompt Engineering
- RAG
- Embeddings
- Vector Search
- LLM APIs
- AI Agents
- AI Workflows
- Semantic Search
- Model Evaluation
AI Tools
- GitHub Copilot
- Cursor AI
- Windsurf
- Claude Code
- ChatGPT Enterprise
- OpenAI SDKs
- Azure AI Studio
- Amazon Bedrock
Security
- OAuth2
- JWT
- SAML
- API Security
- OWASP Best Practices
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- 7+ years of Java backend development experience.
- 2+ years of hands-on experience building AI-enabled applications.
- Strong experience in developing enterprise microservices.
- Experience integrating LLM APIs into production applications.
- Strong understanding of distributed systems and cloud-native architecture.
- Experience working in Agile/Scrum environments.
- Excellent problem-solving and debugging skills.
Preferred Qualifications
- Experience with LangGraph or agentic AI workflows.
- Experience implementing RAG architectures at scale.
- Experience with MCP (Model Context Protocol) integration.
- Familiarity with AI evaluation frameworks.
- Knowledge of AI guardrails, safety, and responsible AI practices.
- Experience with multimodal AI models (text, image, audio).
- Experience building AI copilots for enterprise applications.
- Cloud certifications (AWS, Azure, or Google Cloud Platform).
- Kubernetes certification is a plus.
Nice-to-Have Skills
- Python for AI/ML integration
- Neo4j or Knowledge Graphs
- Apache Spark
- Airflow
- Elasticsearch/OpenSearch
- Redis
- Temporal.io
- Camunda
- Event Sourcing
- CQRS Architecture
Soft Skills
- Strong communication and collaboration skills.
- Ability to translate business requirements into scalable technical solutions.
- Strong analytical and troubleshooting abilities.
- Passion for learning emerging AI technologies.
- Experience mentoring junior developers and conducting code reviews.
What You'll Build
- AI-powered enterprise applications
- Intelligent document processing systems
- AI chatbots and virtual assistants
- Retrieval-Augmented Generation (RAG) platforms
- AI copilots for internal business users
- Semantic search and knowledge management systems
- Scalable backend APIs supporting Generative AI applications
- Multi-agent AI workflows integrated with enterprise platforms
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