Python Engineer

Python Engineer / Generative AI Developer (LLM & Agentic AI)

Experience: 4 - 8 Years
Location: Indore

Employment Type: Full-Time

Job Summary

We are seeking a highly skilled Python Engineer / Generative AI Developer with 4 to 8 years of experience in software development, AI/ML, and modern Generative AI technologies. The ideal candidate should possess strong expertise in Python development, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI frameworks, and cloud-based deployment environments.

The role involves designing, developing, and deploying enterprise-grade AI solutions leveraging cutting-edge Generative AI technologies to solve real-world business challenges in the Manufacturing domain. The candidate will work closely with AI Architects, Data Scientists, Data Engineers, and Product Owners to build scalable, secure, and production-ready AI applications.

Key Responsibilities

Generative AI & LLM Development

• Design, develop, and implement advanced Generative AI solutions using Large Language Models (LLMs).
• Build intelligent AI assistants, copilots, and autonomous agents using Agentic AI architectures.
• Develop and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise knowledge retrieval.
• Design prompt engineering strategies and evaluate LLM responses for accuracy, relevance, and safety.
• Fine-tune foundation models and open-source LLMs where required.

AI/ML Engineering

• Develop and deploy machine learning and deep learning models using frameworks such as:
• PyTorch
• TensorFlow
• Hugging Face Transformers
• Build NLP solutions including:
• Text Classification
• Information Extraction
• Conversational AI
• Semantic Search
• Document Intelligence
• Perform model evaluation, testing, optimization, and performance tuning.

Python Application Development

• Develop scalable backend services and AI-driven applications using Python.
• Build RESTful APIs and microservices using FastAPI.
• Integrate AI models with enterprise applications and business workflows.
• Ensure clean, reusable, and maintainable code following software engineering best practices.

Agentic AI & Orchestration

• Design and implement autonomous AI agents capable of reasoning, planning, and executing tasks.
• Develop multi-agent workflows for complex enterprise use cases.
• Leverage frameworks such as:
• LangChain
• LangGraph
• LlamaIndex
• CrewAI
• AutoGen
• Integrate external tools, APIs, memory management, and function calling capabilities.

Cloud & DevOps

• Deploy AI applications and services across cloud environments:
• Microsoft Azure
• AWS
• Google Cloud Platform (GCP)
• Implement CI/CD pipelines for automated deployment and monitoring.
• Utilize Docker containerization for packaging and deployment.
• Collaborate with DevOps teams to ensure high availability and scalability.

Performance Optimization

• Optimize latency, throughput, and scalability of AI solutions.
• Implement caching, vector search optimization, and efficient retrieval mechanisms.
• Monitor model performance and continuously improve solution effectiveness.
• Address production issues and ensure system reliability.

Research & Innovation

• Stay updated with the latest advancements in:
• Generative AI
• Foundation Models
• Agentic AI
• Deep Learning
• AI Governance
• Evaluate emerging tools and frameworks for enterprise adoption.
• Contribute to innovation initiatives and proof-of-concept developments.

Required Technical Skills (Must Have)

Programming & Software Engineering

• Strong proficiency in Python programming.
• Solid understanding of Data Structures, Algorithms, and Object-Oriented Programming.
• Experience building production-grade applications.

Artificial Intelligence & Machine Learning

• Hands-on experience with:
• Machine Learning
• Deep Learning
• Natural Language Processing (NLP)
• Experience developing and deploying AI/ML models.

Large Language Models (LLMs)

• Working experience with one or more LLMs:
• Strong understanding of prompt engineering and model evaluation.

Retrieval-Augmented Generation (RAG)

• Hands-on experience building RAG systems from scratch.
• Experience with:
• Vector Databases
• Embedding Models
• Semantic Search
• Knowledge Retrieval Architecture

Agentic AI

• Experience developing AI agents capable of task orchestration and autonomous decision-making.
• Knowledge of multi-agent systems and complex workflow orchestration.

LLM Frameworks

• Expert-level hands-on experience with:
• LangChain
• LlamaIndex
• Experience in:
• Chains
• Agents
• Memory
• Tool Integration
• Retrieval Workflows

API & Backend Development

• Strong experience with FastAPI.
• Development of scalable RESTful APIs and microservices.

Cloud & DevOps

• Experience with Azure, AWS, or GCP.
• CI/CD implementation experience.
• Docker containerization and deployment.

Education

• Bachelor's or Master's degree in:
• Computer Science
• Artificial Intelligence
• Data Science
• Information Technology
• Related Engineering Discipline