Python Lead with AI Expertise

LOCATION: Hyderabad

Mode: Work from Office only

Job Description:

We are seeking a highly motivated Python Developer with a strong foundation in AI applications to join our team. The ideal candidate will possess expertise in Python programming, a deep understanding of AI-related libraries and frameworks, and the ability to develop and deploy AI-driven solutions. This role requires proficiency in developing APIs, working with key Python libraries for data handling and AI, and implementing large language models (LLMs) and related technologies.

Key Responsibilities:

Module 1: Python Basics

• Develop robust and scalable Python applications using variables, data types, and control flow mechanisms.
• Create and manage Python functions, modules, and object-oriented programming (OOP) constructs.
• Implement file handling and I/O operations.
• Build and integrate APIs using Flask and Django.
• Handle data structures like lists, dictionaries, sets, and tuples, and apply list comprehensions and lambda functions effectively.
• Debug and manage error handling in Python applications.

Module 2: Data Handling and Visualization

• Utilize NumPy for numerical computations, array manipulation, and data preprocessing.
• Leverage Pandas for structured data handling, cleaning, and transformation.
• Visualize data using Matplotlib and Seaborn to support AI workflows.

Module 3: Deep Learning Libraries

• Develop simple neural networks using TensorFlow and PyTorch.
• Understand the differences between TensorFlow and PyTorch and apply them to appropriate use cases.

Module 4: Integration with LLM APIs

• Set up and access popular LLM APIs such as OpenAI, Hugging Face, and Anthropic.
• Create scripts to handle API calls, parse JSON responses, and manage token limits.
• Write and refine prompts to optimize LLM outputs for specific applications.

Module 5: AI Agents Development

• Build Python-based AI agents for applications like chatbots, text summarization, and data-driven decision-making.
• Incorporate memory and context into AI agents for enhanced functionality.
• Deploy AI agents locally or on the cloud, ensuring scalability and efficiency.

Module 6: Generative AI and Prompt Engineering

• Implement generative AI solutions for text, image, and code generation.
• Write and optimize effective prompts, leveraging techniques like instruction-tuning and chain-of-thought prompting.

Module 7: Vector Databases and RAG Systems

• Work with vector databases such as Pinecone, Weaviate, Milvus, and Chroma.
• Design and implement Retrieval-Augmented Generation (RAG) systems to enhance LLM-based applications.

Module 8: Multi-Agent Systems

• Develop multi-agent systems using frameworks like LangChain, LlamaIndex, AutoGen, and Crew AI.
• Design communication and coordination mechanisms for distributed problem-solving.

Module 9: Tools for Coding Assistance

• Utilize tools like Cursor.ai for code auto-completion, debugging, refactoring, and querying.
• Integrate AI-powered coding tools with development environments such as VS Code and JetBrains.

Qualifications:

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Proven experience in Python programming and AI applications.
• Familiarity with key libraries and frameworks: NumPy, Pandas, TensorFlow, PyTorch, Flask, Django, Matplotlib, and Seaborn.
• Experience working with LLMs and APIs (OpenAI, Hugging Face, etc.).
• Strong understanding of generative AI concepts and prompt engineering.
• Knowledge of vector databases and RAG systems.
• Experience deploying AI solutions in cloud environments.

Preferred Skills:

• Hands-on experience with LangChain and LlamaIndex frameworks.
• Understanding of ethical considerations in AI development, including bias, transparency, and accountability.
• Ability to design and implement scalable multi-agent systems.
• Proficiency with coding assistance tools like Cursor.ai.