AI Full stack Developer

Work Location: Chennai
Experience: 6-8 years
Education Qualification: Bachelor’s Degree

Required Skills:

Technical Leadership

• Lead design, architecture, and development of AI-driven applications using GenAI and Agentic AI frameworks.
• Mentor and guide a team of developers, ensuring high-quality code and best practices.
• Collaborate with product managers, data scientists, and stakeholders to define technical roadmaps.

AI/ML Development

• Design, develop, and implement ML/DL models for predictive analytics, NLP, computer vision, and generative AI use cases.
• AI/ML Frameworks: TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers
• Build and integrate LLMs, GenAI models, and agent-based AI workflows into enterprise solutions.
• Fine-tune, prompt-engineer, and optimize LLMs (OpenAI, Anthropic, Llama, etc.) for business use cases.
• Design and implement multi-agent orchestration systems for intelligent automation.

Fullstack Development

• Develop scalable web applications using React.js / Angular / Vue.js (frontend) and Python (Django / Flask / FastAPI / Node.js) (backend).
• Integrate AI/ML APIs, microservices, and databases (SQL & NoSQL).
• Ensure security, scalability, and performance of deployed applications.

Cloud & MLOps

Monitor and optimize model performance in production.

Deploy and manage AI applications on AWS / Azure / GCP.

Implement CI/CD, containerization (Docker, Kubernetes), and model deployment pipelines.

• Define end-to-end architecture for GenAI & Agentic AI solutions
• Design scalable and secure AI pipelines including data ingestion, model training, fine-tuning, deployment, and monitoring.
• Architect multi-agent AI systems leveraging frameworks like LangChain, AutoGen, LlamaIndex, or similar.

Hands-on Development

• Build and optimize AI applications in Python using frameworks such as PyTorch, TensorFlow, Hugging Face Transformers.
• Implement and integrate LLMs, embeddings, RAG (Retrieval-Augmented Generation), vector databases (Pinecone, FAISS, Weaviate, Milvus).
• Develop autonomous AI agents for workflow automation, reasoning, and decision-making.

Innovation & Strategy

• Evaluate and recommend emerging GenAI & Agentic AI frameworks, tools, and platforms.
• Define best practices for prompt engineering, model fine-tuning, safety, compliance, and governance.
• Collaborate with stakeholders to align AI solutions with business goals and enterprise architecture.

Leadership & Mentoring

• Lead technical discussions and provide architectural guidance to engineering teams.
• Mentor data scientists, ML engineers, and software developers in AI best practices.
• Collaborate with product managers and business leaders on solution roadmaps.