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Agentic AI - Java Background
Job in
Arlington, Arlington County, Virginia, 22201, USA
Listed on 2026-07-20
Listing for:
Techyantram Solutions LLC
Full Time
position Listed on 2026-07-20
Job specializations:
-
Software Development
Backend Developer, AI Engineer (Applied/Software), Cloud Engineer - Software, Java Developer
Job Description & How to Apply Below
As a member of our Agentic AI team with a Java background, you will be responsible for developing and implementing innovative AI solutions using cutting‑edge technologies. You will work closely with our team to create AI‑powered applications that drive business growth and enhance user experiences.
Responsibilities- Develop and deploy Java microservices using LangChain4j and Spring AI
- Implement Semantic Kernel for enhanced AI capabilities
- Utilize Retrieval‑Augmented Generation (RAG) for advanced AI functionalities
- Work with Milvus, Qdrant, and Pinecone for efficient data storage and retrieval
- Integrate LLM (Large Language Model) for natural language processing tasks
- Utilize Spring Boot and Spring Cloud for building scalable applications
- Implement Hibernate for database management
- Create and maintain RESTful APIs for seamless communication between services
- Utilize PostgreSQL and No
SQL databases for data storage and retrieval - Work with Vector Databases, including PGVector and Chroma, for AI model storage
- Implement messaging systems such as Kafka and RabbitMQ for real‑time data processing
- Utilize Web Sockets for bidirectional communication between clients and servers
- Deploy applications on cloud platforms such as AWS, Azure, and Google Cloud Platform
- Containerize applications using Docker and manage container orchestration with Kubernetes
- Proficiency in Java programming
- Experience with developing Java microservices
- Knowledge of AI technologies such as RAG, LLM, and Semantic Kernel
- Experience with Spring Boot, Spring Cloud, and Hibernate
- Understanding of RESTful API design and implementation
- Experience with PostgreSQL and No
SQL databases - Familiarity with Vector Databases like PGVector and Chroma
- Experience with messaging systems such as Kafka and RabbitMQ
- Knowledge of Web Sockets for real‑time communication
- Experience with cloud platforms like AWS, Azure, and Google Cloud Platform
- Proficiency in Docker and Kubernetes for containerization and orchestration
- Experience with Milvus, Qdrant, and Pinecone for data storage and retrieval
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