Live opening · Posted 8 days ago
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Description supplied by the original job listing.
Seeking an experienced Python Full-Stack and AI/GenAI Engineer with expertise in Python, React.js, LLMs, RAG, agentic AI, and cloud-native application development. The ideal candidate should have hands-on experience in building scalable full-stack applications, AI-powered solutions, data pipelines, and enterprise-grade GenAI platforms.
Responsibilities:
Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.
Design, develop, and lead Python-based full-stack and GenAI applications.
Build scalable REST APIs and responsive React.js front-end applications.
Develop and optimize RAG pipelines, vector search, and agentic AI workflows.
Design secure authentication and authorization mechanisms.
Build data ingestion and processing pipelines for structured/unstructured data.
Mentor team members and contribute to architecture and technical decisions.
Requirements:
Minimum 3+ years of Python development experience.
Hands-on experience in React.js and AI/GenAI solution development.
Strong problem-solving and scenario-based troubleshooting skills.
15 years of full-time education.
Must-Have Skills:
Python, OOP, Design Patterns, Unit Testing.
Flask, FastAPI, Django REST Framework.
Authentication and Authorization (JWT, OAuth, SSO).
Data Ingestion, Data Pipelines, Large File Handling.
NumPy, Pandas, DataFrames, Prefect.
Performance Tuning and Code Optimization.
SQL, PL/SQL, Data Modeling, Shell Scripting
React.js, Redux, React Hooks, Context API.
REST API Integration (Axios, Fetch).
Jest, React Testing Library
Git, CI-CD.
AI / GenAI Skills
LLM Integration, GenAI Tooling
RAG Pipeline Development and Optimization.
LangChain, LangGraph, and Sentence Transformers.
Hugging Face Transformers
Vector Databases (FAISS, Qdrant, Weaviate).
Embedding Models (OpenAI, BERT, or Similar).
Agentic AI Workflows.
Semantic Search and Vector Search.
Grafana Monitoring and Observability.
Good to Have:
Docker, Kubernetes, Containerization.
AWS-Azure Cloud
Microservices Architecture.
Azure OpenAI, Bedrock, LlamaIndex, MCP
Experience
5-8 yrs
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