As a Senior Software Developer with proficiency in Python and Generative AI, you will act as a technical leader responsible for architecting and deploying production-grade AI systems. Beyond standard coding, this role bridges the gap between AI research and scalable software engineering, focusing on Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic workflows.
Core Responsibilities
System Architecture & Development: Lead the development of scalable backend systems and robust architectures for platforms powered by artificial intelligence, ensuring high availability and security.
GenAI Implementation: Build and deploy production-scale Agentic AI workflows and multi-model RAG pipelines using frameworks like LangChain or LlamaIndex.
Model Optimization: Fine-tune LLMs using techniques like LoRA or QLoRA and perform prompt engineering to improve model accuracy and efficiency.
API Development: Develop high-performance RESTful or GraphQL APIs (typically using FastAPI or Flask) to integrate AI models with enterprise applications.
Data & MLOps:
Implement data ingestion and preprocessing mechanisms, while coordinating LLMOps practices such as model versioning, monitoring, and CI/CD for AI services.
Leadership & Mentorship: Provide technical guidance to junior developers, conduct rigorous code reviews, and foster a team-oriented environment adhering to established guidelines.
Technical Skills & Qualifications
Advanced Python: Expert-level proficiency (typically 5-8+ years) in Python, including asynchronous programming (asyncio), OOP, and build patterns.
AI Frameworks: Deep experience with Hugging Face, PyTorch, or TensorFlow, and specialized GenAI libraries like LangGraph or CrewAI.
Vector Databases: Hands-on knowledge of vector search and storage solutions like Pinecone, Weaviate, or FAISS.
Cloud Platforms: Strong experience deploying to cloud environments like AWS, Azure, or GCP.
Data Engineering: Proficiency in data processing libraries such as P