Ai Ml Engineer

Job Title: SSE Python & LLM Integration

About the Role

We are looking for a hands-on technical lead with strong Python expertise and a deep understanding of Large Language Model (LLM) integration to lead the design, development, and deployment of AI-powered solutions. This role requires a balance of technical leadership, architecture design, and hands-on coding to ensure high-quality, scalable, and efficient AI-driven applications.

You will collaborate closely with product, data science, and MLOps teams to integrate LLMs into real-world applications, optimize performance, and guide the team in best practices for AI system design.

Key Responsibilities

• Lead the development and integration of Python-based applications with LLMs (OpenAI, DeepSeek, Anthropic, LLaMA, etc.).
• Architect and implement LLM pipelines including prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and evaluation.
• Design scalable microservices and APIs for AI features.
• Collaborate with MLOps teams to deploy and monitor AI models in production.
• Ensure performance optimization, cost efficiency, and security in LLM workflows.
• Guide the team on Python best practices, code reviews, and technical problem-solving.
• Stay updated on emerging AI/LLM advancements and propose adoption where beneficial.

Required Skills & Experience

• Strong proficiency in Python (FastAPI, Flask).
• Solid experience with LLM integration (OpenAI API, Hugging Face Transformers, LangChain, LlamaIndex).
• Understanding of RAG pipelines (vector databases like Pinecone, Weaviate, FAISS, Milvus).
• Experience with prompt engineering & evaluation techniques.
• Knowledge of MLOps tools (MLflow, Kubeflow, Langfuse) and deployment on AWS/GCP/Azure.
• Familiarity with containerization and orchestration (Docker, Kubernetes).
• Strong grasp of REST APIs, GraphQL, and microservices architecture.
• Knowledge of model fine-tuning and performance optimization.