Technical Lead

Photon , a global leader in AI and digital solutions, helps clients accelerate AI adoption and embrace Digital Hyper-expansion to make tomorrow happen today. We work with 40% of the Fortune 100, enabling them to stay agile and future-ready in an era of converging digital and AI boundaries. Powering billions of touchpoints a day, Photon combines AI management, digital innovation, product design thinking, and engineering excellence to drive lasting transformation for F500 clients. We employ several thousand people across dozens of countries.

Job Title: Technical Lead (Python + Gen AI)

Company: Photon Interactive

Location: Chennai (Work from office) - No remote / Hybrid

Experience: 8+ years

Employment Type: Full-time

Job Summary:

We are looking for a talented Generative AI Developer with strong Python expertise to join our team. The ideal candidate will have hands-on experience in building and deploying AI/ML models, especially in the field of Generative AI (e.g., LLMs, Diffusion Models, Transformers). Youll work closely with data scientists, product managers, and engineering teams to integrate intelligent, generative capabilities into real-world applications.

Key Responsibilities:

• Design, develop, and deploy Generative AI models (e.g., LLMs, GPT, diffusion models, VAEs).
• Fine-tune pre-trained models using Hugging Face, OpenAI, or other frameworks.
• Build data pipelines and APIs to support training and inference.
• Integrate AI functionality into production systems and applications.
• Evaluate and improve model performance, latency, and reliability.
• Stay current with the latest GenAI research and rapidly evolving ecosystem.
• Collaborate with cross-functional teams to understand business requirements and deliver AI-powered solutions.

Must-Have Skills:

• Strong Python programming experience (8+ years).
• Experience with Generative AI frameworks such as Hugging Face Transformers,OpenAI API, or LLamaIndex.
• Mandatory worked in LangChain OR LangGraph, Langwatch
• Experience with LLM fine-tuning prompt engineering, embeddings, or vector databases.
• Understanding of NLP concepts: tokenization, embeddings, attention mechanisms.
• Working knowledge of REST APIs, Docker, and cloud services (AWS/GCP/Azure).