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Mid-level seniority and popular AI/fullstack title increase competition, though LLM specialization partially filters applicants.
Role requires deep ML/LLM expertise, making candidates less transferable across non-AI industries.
Explicit 5+ years, mandatory LLM/ML plus fullstack, AWS, and Kubernetes skills raise filtering strictness.
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Lead design and implementation of AI and ML solutions focusing on Large Language Models (LLMs), including RAG systems, fine-tuning, and prompt engineering.
Integrate AI/ML models into scalable full-stack applications using APIs, microservices, with backend Node.js and frontend React expertise.
Analyze and benchmark AI model performance across datasets and use cases, ensuring AI trustworthiness metrics such as accuracy, interpretability, and robustness.
5+ years of professional experience in AI and full-stack development environments.
Strong experience with Machine Learning, Generative AI, Natural Language Processing using Python, including hands-on work with LLMs.
Proficiency in backend development with Node.js and frontend development with React; experience with Postgres/SQL database design and AWS cloud services.
Work Experience Required: Minimum 5 years in relevant AI and full-stack roles. Notice Period: Not explicitly mentioned in the JD.
Experienced in deploying and integrating enterprise-grade, scalable web applications with containerization technologies like Docker and Kubernetes.
Familiar with AI trustworthiness concepts and responsible AI practices, capable of bridging ML engineering and operational application development.
Comfortable working in a global team environment focused on deploying agentic AI with a strong emphasis on model evaluation and AI agent testing.