Generative Ai Developer

Job description

**Job Title:** Python Engineer/ Gen AI Developer (4-8 yrs experience) **Primary Role & 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 with Docker for packaging and deploying applications. **Key Skills, Experience & Knowledge:** (Must-Have) - Strong programming skills in Python with experience in building ML/NLP applications. - Hands-on experience with Deep Learning, Machine Learning, and Natural Language Processing. - Proficiency in working with LLMs (e.g., GPT,Gemini, LLaMA, Mistral) and RAG architecture. - Experience with Agentic AI frameworks and autonomous agent design. - Familiarity with FastAPI for building RESTful APIs. - Experience with CI/CD pipelines and deploying solutions on Azure 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 with LangChain and/or LlamaIndex for building complex LLM applications, including chains, agents, memory, and tool integration **Key Skills/Knowledge:** (Good to have) - 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 **Key Relationships & Contacts:** - Key interactions: • IT Product Owners, IT Agile Delivery Leads, IT Scrum Masters, AI Architects, Data Engineer.