Primary Responsibilities :

- Design, develop, and deploy production-ready AI/ML solutions for enterprise applications.

- Build and optimize Large Language Model (LLM) applications, AI agents, and Retrieval-Augmented Generation (RAG) pipelines.

- Fine-tune, evaluate, and optimize open-source and commercial AI models for specific business use cases.

- Develop scalable APIs and AI services using Python frameworks such as FastAPI or Flask.

- Build intelligent automation workflows using AI, vector databases, and orchestration frameworks.

- Design and implement machine learning pipelines for data preprocessing, feature engineering, model training, validation, and deployment.

- Collaborate with Product Managers, Architects, UI/UX Designers, and DevOps teams to deliver AI-powered products.

- Optimize model inference performance, latency, and infrastructure costs.

- Mentor junior AI engineers and participate in architecture discussions, technical reviews, and code reviews.

- Research and evaluate emerging AI technologies and recommend adoption where appropriate.

- Ensure AI applications follow security, privacy, and responsible AI best practices.

Technical Requirements :

Programming Languages :

- Strong expertise in Python.

- Good knowledge of SQL.

- Basic understanding of JavaScript or TypeScript for AI integrations.

Artificial Intelligence & Machine Learning :

- Strong experience with Machine Learning, Deep Learning, NLP, and Generative AI.

- Hands-on experience with LLMs such as GPT, Claude, Llama, Qwen, Mistral, or Gemma.

- Experience developing AI Agents and multi-agent workflows.

- Strong understanding of prompt engineering, structured outputs, function calling, and tool integration.

- Experience implementing Retrieval-Augmented Generation (RAG) architectures.

- Knowledge of embedding models and semantic search.