Java Microservice Developer + AI (Immediate Joiner)

**APPLICABLE ONLY FOR IMMEDIATE JOINERS**

Job Specification

Job Title: Java Microservices Developer + AI

Experience: 5+ Years

Location: Gurgaon

Job Summary:

Senior Java Developer

Key Responsibilities:

Java Microservices Development:

• Design, develop, and maintain robust and scalable microservices using

  Java

  ,

  Spring Boot

  , and

  Spring Cloud

  .
• Build RESTful APIs and event-driven services that integrate with cloud platforms and third-party systems.
• Implement service discovery, configuration management, fault tolerance, and API gateways.
• Ensure CI/CD best practices and participate in automated testing and code reviews.
  

AI Integration:

• Collaborate with Data Scientists to integrate AI/ML models (e.g., predictive analytics, NLP, recommendation systems) into microservice architecture.
• Develop APIs and infrastructure for serving ML models using tools like

  TensorFlow Serving

  ,

  SageMaker

  ,

  ONNX

  , or

  custom Dockerized solutions

  .
• Optimize inference pipelines for performance, scalability, and reliability.
• Handle versioning, monitoring, and logging of deployed models.
  

Key Skills:

• Java 8+

  ,

  Spring Boot

  ,

  Spring Cloud

• Microservices architecture

  ,

  RESTful APIs

• AI/ML model integration

  (via REST, gRPC, or containerized deployment)

• Docker

  ,

  Kubernetes

  ,

  CI/CD pipelines

• Messaging systems

  : Kafka, RabbitMQ, or similar

• Database technologies

  : SQL (PostgreSQL, MySQL), NoSQL (MongoDB, Redis)

• Cloud platforms

  : AWS, Azure, or GCP

• Model serving

  : TensorFlow Serving, SageMaker, MLflow, ONNX

• Monitoring

  : Prometheus, Grafana, ELK, or similar

• Version control

  : Git, GitHub/GitLab

• Agile/Scrum methodologies

Preferred Qualifications:

• Experience with

  AI frameworks

  : TensorFlow, PyTorch, Scikit-learn
• Familiarity with

  MLOps

  tools and practices
• Experience building

  AI-powered features

  (e.g., chatbots, anomaly detection, personalization engines)
• Understanding of

  data engineering pipelines

  and

  feature stores

• Exposure to

  security best practices

  in microservices and AI systems

Educational Background:

• Bachelors or Masters degree in Computer Science, Software Engineering, or a related technical field.