Description

Role Overview:

This role focuses on a Java AI Engineer responsible for designing and developing scalable backend applications using modern Java frameworks and microservices architecture. A significant part of the role involves building and deploying advanced AI and Generative AI solutions, integrating large language models, and implementing robust cloud and DevOps practices for deployment and monitoring.

Key Responsibilities:

• Design and develop scalable applications with Java 17/21, Spring Boot, Spring Cloud, and Microservices architecture.
• Develop RESTful APIs and event-driven services using Kafka.
• Implement secure applications adhering to OAuth2, JWT, RBAC, and enterprise security standards.
• Optimize performance, resiliency, and scalability of distributed systems.
• Build and deploy AI-powered applications utilizing OpenAI, Azure OpenAI, Claude, or similar LLM platforms.
• Design and implement Retrieval Augmented Generation (RAG) solutions with Vector Databases.
• Develop AI Agents, managing tool calling, orchestration, memory, and workflow automation.
• Apply prompt engineering, semantic search, embeddings, and context management techniques.
• Integrate enterprise knowledge repositories with AI solutions.
• Develop responsible AI guardrails, validation, and observability frameworks.
• Deploy applications on AWS, Azure, or GCP.
• Build and maintain CI/CD pipelines using GitHub Actions, Jenkins, or GitLab CI.
• Containerize services with Docker and Kubernetes.
• Monitor production systems using Splunk, Grafana, Prometheus, ELK, or Cloud Monitoring solutions.

Required Skills:

• Core Java (Java 17/21), Spring Boot, Spring Cloud, Hibernate/JPA.
• REST APIs, Microservices, Kafka.
• SQL & NoSQL Databases (PostgreSQL, MongoDB, DynamoDB, Redis).
• LLM Integration (OpenAI / Azure OpenAI APIs), Prompt Engineering.
• RAG Architecture, AI Agents, LangChain / LlamaIndex.
• Embeddings & Semantic Search, Vector Databases (Pinecone, Chroma, Weaviate, Milvus).
• MCP (Model Context Protocol), Function Calling & Tool Usage.
• Cloud & DevOps (AWS / Azure / GCP, Docker, Kubernetes, CI/CD Pipelines, GitHub Actions / Jenkins).

Qualifications:

• 6-8 years of experience in Java and AI/Generative AI development.

Preferred Skills:

• Terraform
• Snowflake
• NVIDIA NIM
• Agentic AI Frameworks
• MLOps / LLMOps
• FastAPI or Python
• GraphRAG
• Knowledge Graphs
• Multi-Agent Systems

Key Skills

Education

Any Graduate