GenAI Developer

Design, develop, and deploy enterprise Generative AI applications using Azure OpenAI Services.

Build Retrieval-Augmented Generation (RAG) pipelines using embeddings and vector databases.

Develop scalable REST APIs using FastAPI and Flask.

Integrate Vision LLMs for image, document, and multimodal understanding.

Build document processing pipelines using PyMuPDF for PDF extraction, parsing, and preprocessing.

Implement semantic search using FAISS Vector Database.

Engineer prompts and optimize LLM responses for enterprise use cases.

Develop AI-powered chatbots, document Q&A, summarization, and intelligent automation solutions.

Optimize AI models for latency, scalability, and cost efficiency.

Integrate AI solutions with enterprise applications and cloud services.

Implement monitoring, evaluation, and experimentation frameworks using Opik or similar LLM observability tools.

Collaborate with product managers, architects, data scientists, and software engineers to deliver AI solutions.

Ensure AI applications follow security, governance, and responsible AI best practices.

Required Skills

Generative AI

Large Language Models (LLMs)

Prompt Engineering

Retrieval-Augmented Generation (RAG)

Embeddings

Semantic Search

AI Agents

Function Calling

Context Management

Model Evaluation

Cloud & AI Platforms

Azure OpenAI Service

Azure AI Services

Azure Cognitive Search (preferred)

Azure Storage

Azure Functions (preferred)

Programming

Python (Advanced)

FastAPI

Flask

REST API Development

Async Programming

AI Frameworks & Libraries

LangChain

LlamaIndex

PyMuPDF

FAISS Vector Database

Vision LLMs

OpenAI SDK

Transformers (preferred)

Development Tools

Visual Studio Code (VS Code)

PyCharm

Git

GitHub/Azure DevOps

Docker

Observability & Evaluation

Opik

Prompt evaluation

LLM monitoring

Experiment tracking

Performance benchmarking

Required Experience

5–10 years of software development experience with strong Python expertise.

Minimum 2–4 years of hands-on experience in Generative AI and LLM-based application development.

Experience implementing enterprise RAG architectures.

Strong experience with Azure OpenAI.

Experience integrating Vision LLMs for document and image processing.

Hands-on experience with vector databases such as FAISS.

Experience building production-ready AI APIs using FastAPI or Flask.

Experience processing large PDF/document repositories using PyMuPDF.

Experience with AI evaluation and observability tools such as Opik.

Experience deploying AI applications in cloud environments.

Nice-to-Have Skills

LangGraph

AutoGen/CrewAI

Azure AI Search

Cosmos DB

PostgreSQL

Redis

Kubernetes

MLflow

Hugging Face

OCR (Azure Document Intelligence, Tesseract)

CI/CD pipelines

MLOps

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