Role Description Senior AI Engineer - Job Title: Senior AI Engineer Experience: 6-10+ Years Location: Hybrid/Onsite Domain: Healthcare (Preferred) Job Summary We are seeking a highly skilled Senior AI Engineer to design, develop, and deploy AI/ML solutions that solve complex business problems. The ideal candidate will have strong expertise in machine learning, generative AI, large language models (LLMs), MLOps, and cloud-based AI platforms, with a passion for building scalable and production-ready AI systems.

Key Responsibilities Design, develop, and deploy machine learning and Generative AI solutions. Build and optimize AI applications using LLMs, NLP, and deep learning frameworks. Develop AI-powered chatbots, copilots, recommendation engines, and intelligent automation solutions.

Fine-tune, evaluate, and monitor machine learning and foundation models. Implement RAG (Retrieval-Augmented Generation) architectures and vector databases. Collaborate with business stakeholders, architects, data scientists, and engineering teams to translate requirements into AI solutions.

Establish MLOps practices for model deployment, monitoring, and lifecycle management. Ensure AI solutions meet security, compliance, scalability, and performance standards.



Mentor junior AI engineers and contribute to AI best practices and innovation initiatives.

Required Skills Strong experience in Python and AI/ML development. Hands-on expertise with Generative AI, LLMs, Prompt Engineering, and AI Agents.

Experience with TensorFlow, PyTorch, Scikit-learn, LangChain, or LlamaIndex. Knowledge of NLP, Deep Learning, Computer Vision, and predictive analytics.

Experience with vector databases such as Pinecone, FAISS, Chroma, or Azure AI Search. Solid understanding of MLOps, CI/CD, model deployment, and monitoring.

Experience with cloud platforms such as Azure AI, AWS AI/ML, or Google Cloud AI. Familiarity with REST APIs, microservices, and containerization technologies (Docker/Kubernetes).

Preferred Qualifications Experience in Healthcare or Health Insurance domain. Knowledge of Responsible AI, AI Governance, and Model Risk Management. Azure AI Engineer Associate, AWS ML Specialty, or equivalent AI certifications.

Experience leading AI solution delivery in enterprise environments.

Education Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.

Skills Generative AI, Agentic AI, REST, Machine Learning, Google Cloud Platform, Prompt Engineering, NLP, LLMs

📌 ML Engineer II (Thiruvananthapuram)
🏢 UST
📍 Thiruvananthapuram