Dear Candidates , We are hiring for the below role . You may share resume to [email protected] Position: Tech Lead / Full Stack Engineer (Python, ReactJs, AWS Serverless, SAM)

Qualifications:
• Bachelor’s or master’s degree in computer science or related field.
• 4+ years of experience in Software Engineering/Development
• 3+ years of experience in Python
• 3+ years of experience in ReactJs
• 2+ years of experience in AWS, Graphql (AppSync) ,SAM, services
- Lambda, Glue, Cognito, Bedrock, AppSync & Amplify
• 1+ years of experience in Vector DB & LLM (optional, added advantage)

Requirements:
Backend (Python):
• Solid experience in Python with Flask / FastAPI frameworks.
• Experience in Microservices developments using AWS Lambda
• Experience in data processing pipelines using PySpark in AWS Glue
• Strong knowledge of relational databases like PostgreSQL or MySQL.
• Experience with NumPy and Pandas for data processing.
• Knowledge of Celery, Redis/RabbitMQ/ AWS SQS message queues for asynchronous task processing. Frontend (React.js):
• Strong hands-on experience in React.js, including Redux, Hooks, Context API.
• Proficiency in JavaScript (ES6+) and TypeScript.
• Proficiency in writing reusable and scalable React components.
• Strong knowledge of JavaScript (ES6+), TypeScript, HTML5, CSS3, and responsive UI design.
• Experience with frontend testing frameworks like Jest, React Testing Library. General & DevOps

Skills:
• Experience with CI/CD pipelines
• Good understanding of Git workflows and version control.
• Knowledge of API documentation tools like Swagger/OpenAPI.
• Familiarity with Agile methodologies like Scrum/Kanban & Jira project management tool. Roles &

Responsibilities:
Backend Development:
• Design, develop, and maintain RESTful APIs using Flask or FastAPI.
• Develop microservices using AWS Lambda functions and ETL jobs using AWS Glue & PySpark
• Cleanse, transform, and analyze complex datasets to support business insights and analytics using PySpark.




• Optimize PySpark jobs for performance and scalability.
• Work with Pandas & NumPy for data transformation and analytics. Frontend Development:
• Build modern, scalable, and maintainable React.js applications.
• Develop responsive UI components and integrate with backend APIs.
• Implement state management using Redux/Context API.
• Write clean, efficient, and reusable code following best practices.
• Optimize performance, accessibility, and frontend security. AWS: 1. Serverless Application Development (AWS SAM & Lambda)
• Design and deploy serverless applications using AWS SAM (Serverless Application Model) to automate infrastructure provisioning.
• Develop, test, and maintain AWS Lambda functions for real-time data processing, microservices, and backend automation. 2. Data Engineering with AWS Glue
• Create ETL pipelines with AWS Glue to transform, clean, and catalog structured and semi-structured data.
• Develop Glue Jobs using PySpark and monitor performance, scaling, and job triggers.
• Integrate Glue with data lakes and other AWS data sources S3, and Aurora. 3. Authentication and Access Control (AWS Cognito)
• Implement secure user authentication and authorization using AWS Cognito (user pools and identity pools).
• Customize token policies, integrate social logins (OAuth2, SAML), and manage identity federation. 4. AWS Bedrock & LLMs (Optional)
• Utilize AWS Bedrock to build, test, and fine-tune LLM-powered applications using models like Anthropic Claude, Meta Llama, or Amazon Titan.
• Design prompt engineering strategies, fine-tuning workflows, and RAG (Retrieval
- Augmented Generation) architectures. 5.



GraphQL API Design (AWS AppSync)
• Design scalable GraphQL APIs with AWS AppSync to simplify front-end/backend integration.
• Implement resolvers using Lambda, DynamoDB, and Aurora Serverless data sources.
• Handle schema stitching, caching, real-time subscriptions, and access control. 6. Frontend Integration & DevOps (AWS Amplify)
• Integrate front-end apps (React) with Amplify for CI/CD, hosting, and backend service integration.
• Configure Amplify with GraphQL endpoints (AppSync), Cognito auth, and storage modules.
• Manage deployment pipelines and environment-specific builds. Vector Store Design & Search (added advantage)
• Design schema for storing dense vector embeddings from LLMs or NLP pipelines.
• Integrate vector DBs with LLMs using frameworks like LangChain, or custom RAG workflows. Deployment & Performance Optimization:
• Optimize APIs and database queries for high performance.
• Deploy and manage applications using Docker, Kubernetes (EKS / ECS).
• Implement unit tests, integration tests, and maintain code quality. Technical Leadership:
• Contribute to architectural decisions and collaborate with stakeholders to gather and analyse requirements.
• Mentor junior engineers and contribute to code reviews to ensure high-quality deliverables. Problem-Solving:
• Debug and resolve technical issues and performance bottlenecks in a timely manner.
• Provide innovative solutions to complex technical challenges. Continuous Improvement:
• Stay updated with emerging technologies and incorporate them into existing systems when beneficial.
• Optimize application performance and scalability through regular refactoring and tuning. Collaboration & Best Practices:
• Work with product managers, Business Team, and data engineers.
• Participate in code reviews, sprint planning, and architecture discussions.
• Ensure security best practices in both backend and frontend.
• Maintain technical documentation and API specifications.

📌 Tech Lead (Mumbai)
🏢 Edme Insurance Brokers
📍 Mumbai