Sr. LLM Lead

K&K Talents

Title: Sr. LLM Lead – GenAI / ML (Python, Langchain)

Location: Gurugram, India - Onsite

Employment Type: Contract

Project Duration: 6 Months

Skills: Python, LangChain, Embeddings, Vector DBs (FAISS/Pinecone), Prompt Tuning, AWS/Azure/GCP

Notice Period: Immediate

Role:

We are seeking highly skilled and experienced Senior LLM Engineers with a strong background in Machine Learning and Software Engineering who have transitioned into Generative AI (GenAI) and Large Language Models (LLMs) over the past 3–4 years.

This is a hands-on engineering role focused on designing, building, and deploying GenAI-based systems using state-of-the-art frameworks and tools.

The role involves active participation in architectural design, model fine-tuning, and cross-functional collaboration with business stakeholders, data teams, and engineering leaders to deliver enterprise-grade GenAI solutions.

Responsibilities:

GenAI System Design:

Prompt Engineering & Agent Design:

Technical Roadmapping:

AI Solution Delivery

Cross-functional Collaboration:

System Optimization:

Required Skills:

● 7+ years of total experience in ML/Software Engineering, with 3–4 years of recent experience in LLMs and Generative AI.

● Strong proficiency in Python, LangChain, and SQL.

● Deep understanding of LLM concepts including:

○ Prompt tuning

○ Embeddings

○ Vector databases (e.g., FAISS, Pinecone)

○ Agent frameworks

● Experience working with cloud platforms such as AWS, Azure, or GCP.

● Solid understanding of ML pipelines, deployment strategies, and GenAI use cases.

● Ability to work independently and collaboratively in fast-paced, cross-functional environments.

● Strong verbal and written communication skills; ability to engage effectively with technical and non-technical stakeholders.

Preferred Qualifications

● Minimum 1+ years of hands-on experience specifically in LLM/GenAI-focused implementations.

● Experience delivering ML/AI products from prototyping through to production.

● Familiarity with MLOps, CI/CD, containerization, and scalable AI model deployment.

● Prior involvement in client-facing projects or cross-functional teams building production-ready AI systems.