Senior AI Engineer

7 days ago

Gulbarga, Karnataka, India beBeePython Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

Job Opportunity: AI/LLM Development Lead

We are seeking an experienced professional to lead the development and integration of Python-based applications with Large Language Models (LLMs). The successful candidate will be responsible for architecting and implementing LLM pipelines, designing scalable microservices and APIs, and ensuring performance optimization and security.

Key Responsibilities:

  • Lead the development and integration of Python-based applications with LLMs.
  • 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.

Mandatory Skills:

  • 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.

Optional Skills:

  • Excellent leadership and mentoring abilities. Strong problem-solving and analytical skills.
  • Effective communication with technical and non-technical stakeholders.
  • Ability to work in a fast-paced, evolving AI environment.
  • Experience with agentic AI or Model Context Protocol (MCP). Background in data pipelines (ETL, streaming data).
  • Exposure to AI security & compliance practices. Prior work in scalable enterprise AI products.

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