Python Developer

About the Role

This role focuses on integrating enterprise Java applications with AI/ML capabilities, requiring expertise in both Java and Python.

Key Responsibilities

• Develop secure RESTful APIs utilizing JWT, OAuth2, and Single Sign-On (SSO).
• Implement enterprise integration patterns, API gateways, proxies, caching mechanisms, and distributed messaging platforms like Kafka and RabbitMQ.
• Ensure application quality through rigorous unit testing, integration testing, secure coding standards, performance tuning, and distributed debugging.
• Integrate Java enterprise applications with large language models (LLMs) across platforms such as OpenAI GPT, Azure OpenAI, Google Vertex AI, Anthropic Claude, and AWS Bedrock.
• Design and deploy intelligent assistants, chatbots, document processing pipelines, and workflow automation.
• Ensure strict adherence to data privacy, governance, and security compliance.
• Maintain continuous visibility into application stability and performance using monitoring suites.

Requirements & Tech Stack

• Core Java, Spring Boot, Spring Framework, and Microservices architecture.
• SOLID principles and Object-Oriented Programming.
• Java Collections, multithreading, concurrency, algorithms, and design patterns.
• Python utilizing FastAPI and Flask.
• Retrieval-Augmented Generation (RAG).
• Vector databases including Pinecone, FAISS, ChromaDB, and Milvus.
• Embeddings, semantic search, prompt engineering, AI agents, and function calling.
• Orchestration frameworks such as LangChain, LlamaIndex, and Semantic Kernel.
• Libraries like scikit-learn, TensorFlow, and PyTorch.
• Continuous integration and continuous delivery (CI/CD) pipelines using Jenkins, GitHub Actions, Azure DevOps, or GitLab CI.
• Containerization and orchestration using Docker, Kubernetes, and OpenShift.
• Major cloud platforms: AWS, Azure, Google Cloud.
• Monitoring suites such as Splunk, ELK Stack, Prometheus, Grafana, and AppDynamics.
• Schema design, query optimization, and performance tuning.
• Relational databases: Oracle, MySQL, PostgreSQL.
• NoSQL stores: MongoDB, Couchbase, Redis, Cassandra, and Graph databases.

Qualifications

• Deep expertise in Core Java, Spring Boot, Spring Framework, and Microservices architecture.
• Advanced command over Java Collections, multithreading, concurrency, algorithms, and design patterns.
• Strong Python development skills.
• Advanced practical knowledge of Retrieval-Augmented Generation (RAG), vector databases, embeddings, semantic search, prompt engineering, AI agents, and function calling.
• Familiarity with orchestration frameworks like LangChain, LlamaIndex, and Semantic Kernel.
• Comprehensive understanding of CI/CD pipelines and containerization/orchestration.
• Hands-on experience with Docker, Kubernetes, and OpenShift.
• Experience with major cloud platforms (AWS, Azure, Google Cloud).
• Experience with monitoring suites.
• Data engineering expertise.
• Experience working with a diverse ecosystem of relational databases and NoSQL stores.