AI / Generative AI Engineer (2 Years)

N-Labs; Hyderabad; On-site; INR 450,000 - 850,000; Full time

Job summary

N-Labs in Hyderabad is seeking an AI/Generative AI Engineer with ~2 years of hands-on Python experience to help build production-grade AI applications under technical guidance.

You will develop Python-based Generative AI and LLM applications, construct RAG pipelines, work with LangChain, implement prompt engineering, create REST APIs with FastAPI/Flask, and collaborate with senior engineers to translate requirements into scalable AI solutions.

Qualifications

• 2 years of relevant experience in AI, Data Science, Generative AI, or related software development.
• Strong Python programming and SQL skills.
• Hands-on exposure to LLMs and Generative AI application development.
• Working knowledge of LangChain, RAG, embeddings, and vector databases.
• Knowledge of FastAPI/Flask and REST APIs.
• Basic understanding of AWS and event-driven application patterns.
• Ability to work with structured and unstructured data.

Responsibilities

• Develop Python-based Generative AI and LLM applications.
• Build and maintain RAG pipelines using embeddings, semantic search, and vector databases.
• Work with LangChain and demonstrate working knowledge of LangGraph or equivalent orchestration frameworks.
• Implement prompt engineering, structured outputs, and basic tool/function calling.
• Develop REST APIs using FastAPI or Flask and integrate AI capabilities with backend services.
• Work with databases and structured data using SQL and Python data-processing libraries.
• Support deployment and integration of AI applications using AWS services such as Lambda, S3, SQS, and EC2.
• Participate in LLM response validation, testing, debugging, and regression checks.
• Collaborate with senior engineers and business stakeholders to convert requirements into AI solutions.

Skills

Python

SQL

LLMs

Generative AI

LangChain

RAG

Embeddings

Vector databases

FastAPI/Flask

REST APIs

AWS

Structured data

Unstructured data

Tools

PostgreSQL

MySQL

MongoDB

MSSQL

Job description

We are looking for an AI / Generative AI Engineer with around 2 years of hands-on experience in Python, Generative AI, LLM applications, RAG pipelines, and AI-driven automation. The candidate should be able to contribute to the development of production-oriented AI applications under technical guidance.

Key Responsibilities

• Develop Python-based Generative AI and LLM applications.
• Build and maintain RAG pipelines using embeddings, semantic search, and vector databases.
• Work with LangChain and demonstrate working knowledge of LangGraph or equivalent orchestration frameworks.
• Implement prompt engineering, structured outputs, and basic tool/function calling.
• Develop REST APIs using FastAPI or Flask and integrate AI capabilities with backend services.
• Work with databases and structured data using SQL and Python data-processing libraries.
• Support deployment and integration of AI applications using AWS services such as Lambda, S3, SQS, and EC2.
• Participate in LLM response validation, testing, debugging, and regression checks.
• Collaborate with senior engineers and business stakeholders to convert requirements into AI solutions.

Mandatory Skills

• 2 years of relevant experience in AI, Data Science, Generative AI, or related software development.
• Strong Python programming and SQL skills.
• Hands-on exposure to LLMs and Generative AI application development.
• Working knowledge of LangChain, RAG, embeddings, and vector databases.
• Knowledge of FastAPI/Flask and REST APIs.
• Basic understanding of AWS and event-driven application patterns.
• Ability to work with structured and unstructured data.

Preferred Background

Experience with Pinecone, FAISS, or Chroma; exposure to OpenAI, Anthropic, Llama, or other LLM providers; experience with Streamlit, ECharts, or similar AI application interfaces; exposure to PostgreSQL, MySQL, MongoDB, or MSSQL; and an understanding of LLM evaluation and hallucination mitigation. Candidates should demonstrate practical implementation capability rather than purely theoretical knowledge.