Python Engineer

Role: Python Engineer + LLM 

Experience: 4 to 8 years

Location: Indore

Mode of Interview: Face to Face Inperson ( Walk in Interview)

Date of interview: 12th Sep 2026 (Saturday)

Roles and Responsibilities:

• Design and implement GenAI solutions leveraging LLMs, RAG pipelines, and Agentic AI architectures.
• Develop and fine-tune deep learning models for NLP tasks using frameworks like PyTorch or TensorFlow.
• Build scalable APIs using FastAPI to serve AI models and integrate with enterprise systems.
• Collaborate with data scientists and ML engineers to deploy models using CI/CD pipelines on Azure.
• Optimize model performance and ensure robustness in production environments.
• Stay updated with the latest research and advancements in generative AI and deep learning.
• Scalability & Performance:Ability to write efficient code and consider scalability and latency implications for Gen AI applications.
• Containerization:Practical experience withDockerfor packaging and deploying applications

Key skills:

• Strong programming skills inPythonwith experience in building ML/NLP applications.
• Hands-on experience withDeep Learning,Machine Learning, andNatural Language Processing.
• Proficiency in working withLLMs(e.g., GPT,Gemini, LLaMA, Mistral) andRAGarchitecture.
• Experience withAgentic AIframeworks and autonomous agent design.
• Familiarity withFastAPIfor building RESTful APIs.
• Experience withCI/CD pipelinesand deploying solutions onAzure Cloud, GCP and AWS
• Solid understanding of data structures, algorithms, and software engineering principles.
• Bachelors or masters degree in computer science, AI, Data Science, or related field.
• Retrieval Augmented Generation (RAG):Hands-on experience in building and optimizing RAG pipelines from scratch
• Expert-level proficiency and hands-on experience withLangChainand/orLlamaIndexfor building complex LLM applications, including chains, agents, memory, and tool integration.

Good to have skills:

• Excellent Communication Skills
• Strong Software Engineering Background (Productionizing the models)
• Hands-on experience with data science tools
• Problem-solving aptitude
• Analytical mind and great business sense