Tech Lead – AI & LLM Engineering

xtsworld; Pune District; On-site; INR 1,500,000 - 2,000,000; Full time

Job summary

A leading tech firm is looking for a Tech Lead – AI & LLM Engineering to oversee AI systems design, focusing on LLMs and Agentic AI frameworks. This role involves leading cross-functional teams, ensuring data security, and developing custom AI solutions. The ideal candidate has a strong background in AI/ML, programming skills in Python, and experience with modern AI frameworks. Candidates should hold a degree in Computer Science and be ready to innovate within a collaborative environment.

Qualifications

• Experience with LLM frameworks and architectures.
• Proven leadership in AI development.
• Strong communication and analytical skills.

Responsibilities

• Lead architecture and design of AI-integrated systems.
• Develop and deploy custom LLM models for applications.
• Collaborate with stakeholders for AI opportunities.

Skills

LLMs: GPT, Claude, Llama

RAG architecture

Python (FastAPI, LangChain)

MCP integration

API integration

Education

Bachelor’s or Master’s degree in Computer Science

Tools

Docker

Kubernetes

Vector Databases

Job description

At XTS we are redefining how learning content is created and delivered. We are seeking a highly skilled Tech Lead –AI&LLMEngineering to lead the design and development of next-generation AI systems leveraging Large Language Models (LLMs), Model Context Protocol (MCP), Agentic AI frameworks, and intelligent automation.

Responsibilities

• Lead architecture and end-to-end design of AI-integrated systems using LLMs and modern AI frameworks.
• Develop, fine‑tune, and deploy custom LLM models for domain-specific applications (retrieval, summarization, Q&A, automation, etc.).
• Integrate LLMs with existing products and workflows using APIs, vector databases, and orchestration frameworks.
• Implement Agentic AI workflows for autonomous task execution, decision-making, and context management.
• Work with Model Context Protocol (MCP) for building context-aware AI systems and multi-agent ecosystems.
• Design RAG (Retrieval-Augmented Generation) pipelines using vector databases (Pinecone, Chroma, FAISS, etc.).
• Collaborate with stakeholders to identify opportunities for AI enablement across platforms.
• Ensure data security, prompt safety, and governance in all AI solutions.
• Guide a cross-functional team of engineers and data scientists in developing production-grade AI applications.
• Research and evaluate emerging AI frameworks, APIs, and tools to enhance system capabilities.

Technical Skills & Expertise

Core AI/LLM Skills

• LLMs: GPT, Claude, Llama, Mistral, Gemini, etc.
• RAG architecture, embeddings, and semantic search.
• Agentic AI frameworks (LangGraph, AutoGPT, CrewAI, or similar).
• MCP integration and context orchestration.
• LLMOps (deployment, monitoring, evaluation, and optimization).

Programming & Frameworks

• Python (FastAPI, LangChain, LlamaIndex, HuggingFace Transformers).
• API integration & orchestration using REST / GraphQL.
• Knowledge of microservices, event‑driven design, and containerization (Docker/Kubernetes).

Data & Infrastructure

• Experience with Vector Databases (Pinecone, Chroma, Milvus, Weaviate).Cloud Platforms: AWS / Azure / GCP (preferred: AWS Sagemaker, Bedrock, Azure OpenAI).
• Familiarity with data pipelines, MLOps, and data governance best practices.

Additional Good‑to‑Haves

• Experience with multimodal AI (vision + language).
• Familiarity with OpenAI Assistants API, MCP‑based tools, or Anthropic ecosystem.
• Understanding of ethical AI, safety, and compliance standards.

Soft Skills & Leadership

• Proven ability to lead and mentor technical teams in AI solution development.
• Strong analytical and architectural thinking.
• Excellent communication, documentation, and stakeholder management skills.
• Passion for innovation, research, and continuous learning in AI technologies.

Education

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.
• Certifications in AI/ML, LLMs, or Cloud AI Services are a plus.

Tech Stack: Large Language Models, Agentic AI, MCP, Design RAG, Cloud, Vector Database, Python, Fast API, Microservices, Docker, Kubernetes.

Expected Joining: Within a month.