Application Lead (Full - Stack) - Python + AI / GenAI

Seeking a highly experienced Python + AI/GenAI Application Lead with Python development and AI/GenAI experience. The ideal candidate should have strong practical expertise in designing and delivering enterprise-grade GenAI applications, RAG solutions, Agentic AI workflows, Vector Search platforms, and scalable data processing systems. The role requires a technical leader who can drive architecture, mentor teams, and lead end-to-end solution delivery.
Responsibilities:
Own the technical direction and architecture of custom software solutions, leading teams through design and delivery. Set development standards and ensure code quality, scalability, and performance aligned to business objectives.
Lead the design and development of AI-powered enterprise applications using Python.
Build and deploy GenAI applications with natural language interfaces.
Design and optimize RAG, Text-to-SQL, Semantic Search, and Agentic AI solutions.
Integrate and orchestrate LLMs from OpenAI, Gemini, Anthropic, and similar platforms.
Design and implement scalable data ingestion and processing pipelines.
Develop and manage embeddings, vector stores, and retrieval frameworks.
Establish monitoring, observability, and performance dashboards using Grafana.
Drive technical design decisions, code reviews, mentoring, and best practices.
Collaborate with stakeholders to deliver scalable and secure AI solutions.
Requirements:
5+ years of hands-on Python development experience.
2+ years of AI/GenAI/RAG and LLM application development.
Must Have Skills:
Python and Backend
5+ years of hands-on Python development experience
Python, OOP, Design Patterns, Unit Testing
FastAPI, Flask, Django REST Framework
SQL, Data Modeling, Shell Scripting
Pandas, NumPy, DataFrames
Authentication and Authorization (JWT-OAuth-SSO)
Performance Tuning and Code Optimization
AI/GenAI (Mandatory)
2+ years of hands-on AI/GenAI application development experience
LLM Integration (OpenAI, Gemini, Anthropic, or similar)
GenAI Tooling and Natural Language Interface Development
Agentic AI Workflows
RAG (Retrieval Augmented Generation) Development and Optimization
Text-to-SQL Solutions
LangChain, LangGraph, Sentence Transformers
Hugging Face Transformers
Vector Search and Semantic Search
Embedding Models (OpenAI, BERT, or similar)
Vector Databases (FAISS, Qdrant, Weaviate, or similar)
Create and manage embeddings and vector stores
Design and implement efficient data ingestion and processing pipelines
Grafana Monitoring and Observability
DevOps and Delivery
Git, CI-CD
Enterprise Application Development
Solution Architecture and Technical Leadership
Good to Have:
Azure OpenAI, AWS Bedrock.
LlamaIndex, MCP.
Docker, Kubernetes.
AWS: Azure Cloud.
Microservices Architecture.
Additional Requirements.

Experience
3-5 yrs