Technical Lead-Gen AI

SSJ Solutions; Pune District, Bengaluru, Delhi; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

SSJ Solutions seeks a Technical Lead-Gen AI to drive GenAI application development across multiple cities in India. The role focuses on building robust GenAI solutions using Autogen, LangChain, LangGraph, LlamaIndex, and related frameworks.

The ideal candidate will have strong Python skills, hands-on experience with large language models, cloud platforms, data architectures, and front-end integration for multi-modal AI products.

Qualifications

• Hands-on experience with GenAI frameworks and LLMs.
• Proficient Python coding for GenAI solutions.
• Experience with cloud platforms and data architectures.

Responsibilities

• Application Development: Build GenAI apps from scratch using listed frameworks.
• Python Programming: Develop high-quality, efficient Python code for GenAI solutions.
• Large-Scale Data Handling & Architecture: Design architectures for large-scale data.

Skills

Python programming

GenAI

LLMs

API integration

front-end tech

data modernization

cloud platforms

Tools

Autogen

Crew.ai

LangGraph

LlamaIndex

LangChain

Job description

Job Title: Technical Lead-Gen AI

Experience: 9+ Plus

Location: Delhi / NCR / Bengaluru/ Pune/Hyderabad/Chennai/Mumbai

Area(s) of responsibility

The Technical Lead will focus on the development, implementation, and engineering of GenAI applications using the latest LLMs and frameworks. This role requires hands-on expertise in Python programming, cloud platforms, and advanced AI techniques, along with additional skills in front-end technologies, data modernization, and API integration. The Technical Lead will be responsible for building applications from the ground up, ensuring robust, scalable, and efficient solutions.

Key Responsibilities

1. Application Development: Build GenAI applications from scratch using frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain.
2. Python Programming: Develop high-quality, efficient, and maintainable Python code for GenAI solutions.
3. Large-Scale Data Handling & Architecture: Design and implement architectures for handling large-scale structured and unstructured data.
4. Multi-Modal LLM Applications: Familiarity with text chat completion, vision, and speech models.