AI Engineer

Responsibilities

• Architect, develop, and maintain AI-powered applications using full stack technologies (Node.js, Python/Django, Flask, etc.) and modern frontend frameworks (React, Angular, Vue.js, etc.).
• Design, implement, and integrate AI and ML workflows with OpenAI APIs, Gemini APIs, Tensorflow, HuggingFace, PyTorch, and Langchain.
• Build and manage databases (Vector DBs, MongoDB, PostgreSQL, Firebase, etc.) for flexible, high-availability, and scalable data storage.
• Train, fine-tune, and validate open-source models, and deploy them at scale using best practices in MLOps and DevOps.
• Create and optimize RAG (Retrieval-Augmented Generation) pipelines and develop robust NER (Named Entity Recognition) systems for NLP-driven products.
• Develop and maintain RESTful APIs and services, ensuring seamless integration of AI functionalities.
• Collaborate with backend/frontend developers, and product managers to gather requirements and deliver end-to-end AI-driven solutions.
• Monitor, analyze, and improve the performance of AI systems; identify and mitigate model drift, bias, and performance bottlenecks.
• Research and stay current with the latest trends and innovations in AI, machine learning, software engineering, open-source tools, and cloud environments.
• Adhere to security, privacy, and ethical standards for all data-driven AI products.

Preferred candidate profile

• 3+ years of hands-on experience as an AI Engineer.
• Good understanding of frontend & backend technologies (Node.js, Python, Django, Flask. React, Angular, Vue.js)
• Advanced experience integrating AI/ML libraries, APIs, and platforms: OpenAI APIs, Gemini APIs, Tensorflow, HuggingFace, PyTorch, Langchain, etc.
• Demonstrable experience in training, fine-tuning, and deploying open-source large language model.
• Familiarity with DevOps/MLOps tools (Docker, Kubernetes, MLflow, CI/CD pipelines) is a plus.
• Knowledge of cloud environments (AWS, Azure, GCP) for AI/ML model deployment.
• Analytical skills for model evaluation, data pipeline debugging, and quantitative troubleshooting.
• Excellent communication and teamwork abilities.