AI Lead(Manager)

Role Summary

We are looking for a motivated AI Engineer with hands-on experience in Python and cloud platforms (AWS or Azure) to help design, build, and deploy Generative AI solutions. This role will work closely with senior engineers, data teams, and business stakeholders to build AI-powered applications including LLM integrations, RAG pipelines, prompt workflows, and AI-driven automation solutions. This is a hands-on engineering role, not research-only. Key Responsibilities Generative AI Development

Build and integrate applications that leverage Large Language Models (LLMs). Develop Retrieval-Augmented Generation (RAG) pipelines. Implement prompt engineering techniques and structured output generation. Integrate AI services through APIs such as OpenAI, Azure OpenAI, or AWS Bedrock. Create AI-powered chatbots, assistants, and internal productivity tools that enhance business workflows.

Python Engineering

Write clean, scalable Python code that supports AI workflows. Develop REST APIs using frameworks such as FastAPI or Flask. Work with JSON, structured data, embeddings, and vector stores. Build data processing scripts that feed into AI pipelines.

Cloud Deployment

Deploy AI applications using AWS services such as:

S3 Lambda Bedrock EC2 API Gateway

Deploy AI applications using Azure services such as:

Azure OpenAI Functions Blob Storage App Services

Support containerization using Docker.

Support CI/CD pipelines to ensure smooth and reliable cloud-based operations.

Data & Integration

Work with structured and unstructured data sources.

Build connectors to databases such as:

PostgreSQL MySQL SQL Server

Assist in creating vector databases using:

FAISS Pinecone OpenSearch

Support model evaluation and logging.

Assist in monitoring, testing, and continuously improving AI systems.

Required Skills

8+ years of experience in software engineering or AI development.

Strong command of Python as the primary programming language.

Comfortable working with APIs and JSON-based integrations.

Foundational understanding of Large Language Models and Generative AI.

Familiarity with:

Prompt Engineering Embeddings Vector Search

Hands-on experience with AWS or Azure.

Familiarity with Git and collaborative development workflows.

Preferred Qualifications

• Experience with LangChain, LlamaIndex, or similar frameworks supporting Large Language Model applications.

• Familiarity with Azure OpenAI or AWS Bedrock.

• Practical experience with FastAPI for API development.

• Basic understanding of:

• Retrieval-Augmented Generation (RAG) architecture AI model evaluation techniques MLOps fundamentals

• Experience working with vector databases for embeddings and search functionality.

• Exposure to Databricks.