Back
Strong employer brand and metro location, but niche agentic generative-AI specialization reduces candidate pool.
Highly specialized generative AI, agentic systems, and MLOps skills limit cross-industry portability.
Mandatory 7+ years, 3+ years LLM experience, MLOps and specific tech-stack make filters strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, develop, and deploy advanced agentic generative AI systems and classical ML solutions end-to-end, including production releases and monitoring.
Lead implementation of Model Context Protocol servers/clients and advanced agentic workflows using multimodal foundation models and Retrieval-Augmented Generation pipelines.
Manage full-stack development and MLOps lifecycle on AWS/multicloud, leveraging AI coding agents to accelerate delivery and optimize performance across frontend, backend, and infrastructure.
7+ years of experience in AI/ML engineering and Data Science, including generative AI and agent-based systems.
3+ years hands-on experience with generative large language models and agentic systems.
Proficiency in production-grade Python programming; TypeScript is advantageous but not mandatory.
Degree in Computer Science, Physics, Statistics, Mathematics, or a related field (B.Sc., B.Eng., M.Sc., M.Eng., Ph.D., or equivalent).
Experienced in end-to-end ownership of complex AI solutions combining data science, full-stack engineering, and MLOps.
Strategic thinker with capability to define architectural patterns, consult cross-functionally, and potentially assume Tech Lead responsibilities.
Proficient with cloud-native scalable AI architectures (AWS/multicloud), agentic AI frameworks (LangChain), and advanced data engineering practices.