AI Engineer

About Entropik

Entropik is a Human Insights AI company helping global brands, including Fortune 500 companies, understand human emotions. Through our flagship product, Decode, we combine quantitative and qualitative research in one AI-powered platform, fortified with our patented Emotion AI tech - Facial Coding, Eye Tracking and Voice AI.

If you want to build at the intersection of AI and human psychology, this is the place to do it.

About The Role

AI is moving fast. At Entropik, youll be directing it at some of the most human problems in market research and customer experience.

As an AI Engineer, youll own the full lifecycle of ML and LLM-powered systems that sit at the core of Decode - from architecting RAG pipelines and multi-agent workflows to shipping production-grade inference systems for our proprietary Emotion AI models. This role is for someone who has the seniority to drive technical decisions, mentor others, and shape how AI is built at Entropik.

Youll work closely with product, research and engineering teams in a fast-moving startup environment where your decisions ship to production - not into a backlog.

Location: Chennai – WFO

Key Responsibilities

• Design and implement AI/ML and Generative AI solutions to solve business problems.
• Build and deploy LLM applications, including RAG systems, AI agents, and workflow automation.
• Develop, evaluate, and optimize machine learning and deep learning models.
• Build scalable APIs and production-grade AI systems with high reliability and performance.
• Design and maintain data pipelines, vector databases, and AI infrastructure.
• Establish model evaluation, monitoring, observability, and MLOps practices.
• Collaborate with product, engineering, and business teams to translate requirements into AI solutions.

• 2-3 years of experience in AI/ML engineering, with hands-on experience in Generative AI and LLM applications.
• Strong programming skills in Python and SQL.
• Deep understanding of Machine Learning, Deep Learning, NLP and LLM architectures.
• Experience with RAG, prompt engineering, embeddings, vector databases, and AI agents.
• Proficiency in frameworks such as PyTorch, LangChain, LangGraph, and LlamaIndex.
• Experience with APIs, microservices, Docker, Kubernetes, and cloud platforms (AWS, Azure, or GCP).
• Familiarity with MLOps, CI/CD, model serving, evaluation frameworks, and monitoring.
• Strong system design, problem-solving, communication, and leadership skills.

• Experience fine-tuning open-source models and building multi-agent systems.
• Experience designing scalable, multi-tenant SaaS platforms.
• Contributions to open-source projects, research publications, or AI communities are a plus