-
Design and develop high-performance applications using Java (Spring Boot, Microservices).
-
Integrate AI models via REST APIs, Python services, or cloud AI platforms.
-
Collaborate with data scientists to deploy and optimize ML models in production.
-
Build APIs and microservices that enable intelligent, data-driven features.
-
Implement data pipelines for AI workloads, ensuring scalability and reliability.
-
Evaluate and experiment with GenAI, LLMs, and AI APIs (OpenAI, AWS Bedrock, Vertex AI, OpenAI).
-
Maintain coding standards, CI/CD pipelines, and cloud deployment best practices (AWS, GCP).
-
Troubleshoot performance issues and ensure application reliability.
-
At least 3 years of experience in Java/J2EE development
-
At least 3 years of experience in DB SQL/NoSQL.
-
Strong knowledge of Spring Boot, Microservices, Spring Security, Spring MVC, Spring Data, JPA, Hibernate.
-
Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, scikit-learn).
-
Experience integrating AI APIs (OpenAI, Hugging Face, Google Vertex AI).
-
Hands-on experience designing and integrating microservices using REST APIs and asynchronous messaging (Kafka).
-
High-level knowledge of CI/CD.
-
Familiarity with Generative AI technologies (LLM integration, prompt engineering, AI model APIs).
-
Solid understanding of data structures, algorithms, and software design patterns.
-
Familiarity with Python for ML model interaction or API wrapping.
-
Experience with Docker, Kubernetes, and cloud environments (AWS/GCP/Azure).
-
Exposure to LangChain, LangGraph, RAG architecture, or vector databases (Pinecone, FAISS).
-
Understanding of the machine learning lifecycle (training, testing, deployment).
-
Experience with event-driven systems (Kafka, RabbitMQ).
-
Contribution to AI-based open-source projects or hackathons.
-
Strong analytical and troubleshooting skills.
-
Excellent oral and written communication skills.
-
Ability to independently learn new technologies.
-
Passionate, team player, and fast learner.