GenAI / Python Engineer – LLM & Data Solutions

Role: GenAI / Python Engineer LLM & Data Solutions

Location: Bangalore | Noida | Hyderabad | Gurgaon | Pune

Experience: 5+ Years

Immediate Joiners Only

Key Responsibilities:

1. Python & Programming:

• Implement Python concepts including staticmethod vs classmethod, lambda functions, and list/tuple operations.
• Write efficient code for array-based operations, data validation, and scenario-based problem-solving.
• Apply concepts of deep copy vs shallow copy in real-world workflows.

1. Data Handling & Processing:

• Perform structured and unstructured data manipulation using Python libraries.
• Execute advanced DataFrame operations, including groupby and aggregation tasks.
• Process OCR outputs, handling tabular data, skewness, and distortion in scanned documents.

1. AI / ML / LLM Development:

• Design and implement retrieval-augmented generation (RAG) workflows.
• Apply metrics for evaluating LLM performance.
• Implement agent-based AI workflows, managing long-term vs short-term memory usage.
• Work on production-level GenAI deployment, including model training, fine-tuning, and prompt engineering.

1. Infrastructure & Deployment:

• Design application and system architecture for AI/ML solutions.
• Deploy models using frameworks like Uvicorn, Gunicorn, and containerized environments.
• Ensure scalable, maintainable, and reliable deployment of AI agents.

1. Additional Responsibilities:

• Conduct sentiment analysis using LLMs, including prompt formulation and evaluation.
• Collaborate with cross-functional teams to integrate AI solutions into products.
• Document workflows, architecture diagrams, and project execution plans.

Qualifications:

• Bachelors or Masters degree in Computer Science, Data Science, or related field.
• Strong Python programming skills, with knowledge of advanced features and libraries.
• Hands-on experience with AI/ML frameworks, LLMs, and agentic AI workflows.
• Experience with OCR tools like Tesseract and PaddleOCR.
• Knowledge of data preprocessing, handling skewness, and tabular data extraction.
• Familiarity with production deployment pipelines and architecture considerations.
• Excellent problem-solving, analytical, and communication skills.