Technical AI Lead - LLM/Python

Description :

Experience : Min 6 to 8 Years

Office Timings : Full Time (EST shift 5pm - 1am)

Notice Period : (Immediate Joiner - Only)

Mandate Skills for Technical Lead AI. Hands-on experience :

- Building custom tools, connectors, or model-controller interfaces (e.g., MCP).

Job Role :

We are seeking a highly skilled lead engineer with deep expertise in Agentic AI, autonomous agents, and Large Language Models (LLMs). The ideal candidate has 6+ years of hands-on experience in Python and open-source model ecosystems, with proven ability to design and deploy tailored AI pipelines and work with a wide range of open models (e.g., Qwen, Llama, Mistral, and others).

Required Experience :

1. Strong proficiency in Python

2. Expertise in Agentic AI, agent frameworks, and autonomous orchestration.

3. Hands-on experience with tailored pipelines for LLMs and multi-agent systems.

4. Experience with vLLM, TGI, and model serving infrastructure.

5. Extensive work with open-source LLMs (Qwen, Llama, Mistral, and similar families).

6. Experience with LangChain, LangGraph, and related agent frameworks.

7. Solid understanding of inference optimization, embeddings, vector search, and model integration patterns.

8. Clear Communication Effectively communicates with leadership and peers.

9. Delegation Skills Able to delegate work efficiently and responsibly.

10. Influence & Persuasion : Capable of influencing management and peers toward effective solutions.

11. Multi-agent architectures for analytics, automation, or workflow systems.

Responsibilities :

- Develop tailored LLM pipelines using frameworks such as LangChain, LangGraph, and related ecosystems.

- Deploy and optimize open-source LLMs using vLLM, TGI (Text Generation Inference), and Python-based inference stacks.

- Work with diverse open models (Qwen, Llama, Mistral, etc.) including fine-tuning, evaluation, and integration.

- Implement scalable AI services with robust prompt engineering, autonomous task planning, and tool execution.

- Collaborate with cross-functional teams to define architecture, performance goals, and best practices