Key Responsibilities:
• Design and implement microservice-based applications using Python and
frameworks such as Django, Flask, or FastAPI.
• Develop and maintain RESTful APIs and services with strong understanding of REST
principles and ORM.
• Build feature-rich full stack applications and chatbots using Generative AI APIs and
AI coding tools.
• Implement LLM-powered features using frameworks such as LangChain,
LangChain.js, LangChain4j, Spring AI, LangGraph, LlamaIndex, Autogen.
• Integrate Azure OpenAI Service and work with providers such as OpenAI, Gemini,
Amazon, and Claude.
• Build RAG pipelines, work with vector databases and embeddings, and utilize tools
like LangSmith for basic usage metrics.
• Develop event-driven systems using Azure Service Bus, RabbitMQ, or Kafka for AIpowered workflows.
• Optimize application performance and ensure responsiveness, reliability, and
scalability.
• Implement automated testing, unit testing, and CI/CD pipelines; perform debugging
and code quality improvements.
• Containerize and orchestrate services using Docker and Kubernetes; deploy on
Azure/AWS/GCP (PaaS and IaaS).
• Collaborate cross-functionally with data scientists and ML engineers to integrate
models.
• Follow best practices for security and documentation.
Requirements:
• 6+ years as a full stack or backend developer with proficiency in Python; fair to
strong experience with JavaScript frameworks/libraries (Angular, React).
• Strong software development skills across design, development, testing,
deployment,



and maintenance of large-scale applications.
• Experience with RESTful APIs, asynchronous request handling, and ORM.
• Ability to build feature rich full stack AI integrated applications.
• Knowledge of SQL and NoSQL databases and data storage solutions; data
processing/manipulation and bulk data operations.
• Experience with containers (Docker, Kubernetes) and CI/CD.
• Working experience deploying to Azure, AWS, or GCP.
• Strong unit testing and debugging skills; strong experience with version control (Git).
• Understanding of LLMs, embeddings, vector databases, RAG, multimodal
applications, agentic frameworks (fundamental level).
• Experience with data/ML frameworks and tools (PyTorch, LangChain, Autogen).
• Solid in data structures, architecture, and design; familiarity with Python threading
limitations and multi-process architecture.
• Strong communication, teamwork, and problem-solving skills; adherence to
security practices.

Preferred Qualifications:
• Familiarity with Agile methodologies and cloud-native/serverless patterns (Azure
Functions, AWS Lambda).
• Experience exposing GenAI capabilities via APIs and embedding AI-driven UIs in
Angular/React.
• Experience with observability and basic telemetry for AI applications.
Good To have:
Certifications in AI/ML, Deep Learning and NLP from Learning platforms such as Coursera,
Udemy or equivalent.
Certifications on Cloud Architecture (GCP/Azure/AWS)
Experience building MCP servers or Agent to Agent applications.
Fine tuning LLMs and Hosting LLMs on Premises

📌 AI Engineer : Senior Associate (West Bengal)
🏢 PwC
📍 West Bengal