AI Technical Lead

3 days ago

Chandigarh, Chandigarh, India beBeeTechnical Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Technical Lead Role

The Technical Lead role is responsible for overseeing the development and integration of Python-based applications with Large Language Models (LLMs).

Key Responsibilities:

  • LLM Integration: Lead the integration of LLMs from various providers, including OpenAI, DeepSeek, Anthropic, LLaMA, etc.
  • Pipeline Architect: Design and implement scalable pipelines for LLMs, encompassing prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and evaluation.
  • Microservices & APIs: Develop microservices and RESTful APIs for AI features, ensuring scalability and performance.
  • MLOps Collaboration: Work closely with MLOps teams to deploy and monitor AI models in production, focusing on performance optimization, cost efficiency, and security.
  • Team Guidance: Mentor junior team members on Python best practices, code reviews, and technical problem-solving.
  • Technological Advancements: Stay updated on emerging AI/LLM advancements and propose adoption where beneficial.

Required Skills

  • Python Proficiency: Strong expertise in Python, with experience in frameworks like FastAPI and Flask.
  • LLM Experience: Solid understanding of LLM integration, including OpenAI API, Hugging Face Transformers, LangChain, and LlamaIndex.
  • RAG Pipelines: Familiarity with RAG pipelines and vector databases like Pinecone, Weaviate, FAISS, and Milvus.
  • MLOps Tools: Knowledge of MLOps tools, such as MLflow, Kubeflow, and Langfuse, along with deployment on cloud platforms like AWS, GCP, and Azure.
  • Containerization & Orchestration: Experience with containerization using Docker and orchestration using Kubernetes.
  • REST APIs & Microservices: Strong grasp of REST APIs, GraphQL, and microservices architecture, with knowledge of model fine-tuning and performance optimization.

Preferred Qualifications

  • Leadership & Communication: Excellent leadership and mentoring abilities, with strong problem-solving and analytical skills.
  • Effective Stakeholder Communication: Ability to communicate effectively with both technical and non-technical stakeholders.
  • Fast-Paced Environment: Capacity to work in a fast-paced, evolving AI environment.
  • Agentic AI & MCP: Experience with agentic AI or Model Context Protocol (MCP), with background in data pipelines (ETL, streaming data).
  • AI Security & Compliance: Familiarity with AI security & compliance practices, with prior work in scalable enterprise AI products.

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