Develop and enhance custom software solutions by designing, coding, and improving components across various systems and applications. Leverage modern frameworks and agile methodologies to deliver scalable, high-performance solutions meticulously crafted for specific business requirements.

Seeking an experienced Python and AI/GenAI Engineer adept at creating enterprise-grade GenAI applications, intelligent search functionalities, Agentic AI workflows, and robust data processing pipelines. A strong foundation in LLMs, RAG, Vector Databases, and contemporary AI frameworks is essential.

Design, develop, and maintain sophisticated AI-powered applications using Python. Build enterprise-grade GenAI solutions, integrating LLMs and Natural Language Interfaces. Develop and optimize Retrieval-Augmented Generation (RAG) systems, Text-to-SQL capabilities, semantic search, and Agentic AI workflows. Engineer and implement scalable data ingestion and processing pipelines. Seamlessly integrate AI models with existing enterprise applications and APIs. Monitor, troubleshoot, and fine-tune AI application performance for optimal results. Contribute significantly to architectural decisions and provide guidance to team members.

Possess 4+ years of dedicated Python development experience. Demonstrate 2+ years of hands-on experience with AI-GenAI-RAG and LLM application development. Proficiency in Python, Object-Oriented Programming (OOPs), Design Patterns, and Unit Testing. Familiarity with web frameworks like FastAPI, Flask, and Django REST Framework. Strong SQL, Data Modeling, and Shell Scripting skills. Experience with Pandas and NumPy for data manipulation. Understanding of Authentication & Authorization mechanisms (JWT, OAuth, SSO). Proven experience integrating with Large Language Models (LLMs) from providers like OpenAI, Gemini, or Anthropic. Expertise in Vector Search, Semantic Search, and Agentic AI Workflows. Skilled in GenAI Tooling and Natural Language Interface Development. Experience in RAG Pipeline Development & Optimization and Text-to-SQL Systems. Familiarity with libraries such as LangChain, LangGraph, and Sentence Transformers. Knowledge of Hugging Face Transformers and embedding models. Proficiency with Vector Databases (e.g., FAISS, Qdrant, Weaviate) and managing embeddings/vector stores. Experience with Grafana for monitoring and observability. Proficiency in Git and CI/CD practices.