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Java Backend + AI Agent Developer

Jade Global
Pune, IND
Full-time
Mid · 5–8 years experience
Onsite
Discovered 3 weeks ago
awsazuredockergcpjavakubernetes

Full Job Posting

Java Backend Engineering

Develop, optimize, and maintain high-performance backend applications using Java (8/11/17).

Build robust microservices using Spring Boot / Spring Cloud.

Design scalable RESTful APIs and event-driven architectures.

Implement secure, highly available, low-latency backend systems.

Work with both relational and NoSQL databases such as MySQL, PostgreSQL, MongoDB, Redis.

Agentic AI Development

Build and integrate AI agents using frameworks such as:

LangChain / LangGraph

OpenAI Assistants / ReAct / AutoGen

HuggingFace, LlamaIndex, or custom agentic frameworks

Develop advanced agentic workflows including:

Tool calling and function calling

Task planning and retrieval-augmented generation (RAG)

Dynamic reasoning and multi-agent collaboration

Integrate leading LLMs (GPT, Claude, Llama, Mistral, etc.) into Java-based systems.

Build workflows and pipelines for prompt engineering, model orchestration, and inference.

Required Skills

  • 5–8 years of experience in Core Java, concurrency, multithreading, and performance tuning.
  • Strong expertise in Spring Boot, REST APIs, and microservices architecture.
  • Proficiency in SQL/NoSQL databases and integrating real-time data streams.
  • Solid understanding of LLMs, RAG, embeddings, and vector databases.
  • Practical experience building AI agent pipelines.
  • Hands-on experience with OpenAI API, LangChain, or similar frameworks.
  • Knowledge of prompt engineering and model fine-tuning techniques.
  • Demonstrated experience deploying AI-driven or agentic systems in production.
  • Familiarity with vector databases such as Pinecone, FAISS, Milvus, Weaviate.
  • Experience with cloud ecosystems ( AWS, Azure, GCP ) and containerization tools ( Docker, Kubernetes ).

Desirable Qualifications

Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.

Working knowledge of Python for interacting with core AI/ML services or models.

Experience with modern vector databases such as Weaviate, Pinecone, Chroma, etc.

Qualifications

  • 5–8 years of experience in Core Java, concurrency, multithreading, and performance tuning.
  • Strong expertise in Spring Boot, REST APIs, and microservices architecture.
  • Proficiency in SQL/NoSQL databases and integrating real-time data streams.
  • Solid understanding of LLMs, RAG, embeddings, and vector databases.
  • Practical experience building AI agent pipelines.
  • Hands-on experience with OpenAI API, LangChain, or similar frameworks.
  • Knowledge of prompt engineering and model fine-tuning techniques.
  • Demonstrated experience deploying AI-driven or agentic systems in production.
  • Familiarity with vector databases such as Pinecone, FAISS, Milvus, Weaviate.
  • Experience with cloud ecosystems ( AWS, Azure, GCP ) and containerization tools ( Docker, Kubernetes ).
  • Desirable Qualifications
  • Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
  • Working knowledge of Python for interacting with core AI/ML services or models.
  • Experience with modern vector databases such as Weaviate, Pinecone, Chroma, etc.

Responsibilities

  • Develop, optimize, and maintain high-performance backend applications using Java (8/11/17).
  • Build robust microservices using Spring Boot / Spring Cloud.
  • Design scalable RESTful APIs and event-driven architectures.
  • Implement secure, highly available, low-latency backend systems.
  • Work with both relational and NoSQL databases such as MySQL, PostgreSQL, MongoDB, Redis.
  • Build and integrate AI agents using frameworks such as:
  • LangChain / LangGraph
  • OpenAI Assistants / ReAct / AutoGen
  • HuggingFace, LlamaIndex, or custom agentic frameworks
  • Develop advanced agentic workflows including:
  • Tool calling and function calling
  • Task planning and retrieval-augmented generation (RAG)
  • Dynamic reasoning and multi-agent collaboration
  • Integrate leading LLMs (GPT, Claude, Llama, Mistral, etc.) into Java-based systems.
  • Build workflows and pipelines for prompt engineering, model orchestration, and inference.

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