Back
Tier-1 brand, senior role in hot LLM space, and metro location increase applicant competition.
Specialized LLM, RAG and agent engineering skills limit transferability outside AI-focused organizations.
Explicit 5-year minimum plus mandatory LLM, agent, Python, Kubernetes and microservices expertise enforces strict shortlisting.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Build and optimize a GPU-accelerated, scalable Retrieval Augmented Generation (RAG) pipeline using Agentic AI and NVIDIA Nemotron models, focusing on accuracy, relevance, grounding, and performance.
Design and implement AI agents for reasoning, planning, multi-step execution, and tool/service collaboration within the RAG workflow.
Develop, deploy, and maintain end-to-end RAG microservices architecture from local environments to enterprise Kubernetes clusters, including driving continuous system improvements and collaborating with teams and partners.
5 years of professional software engineering experience with deep expertise in Python and AI applications.
Bachelor’s or Master’s degree (or equivalent experience) in Computer Science, Electrical Engineering, Data Science, Artificial Intelligence, or related fields.
Hands-on experience building and deploying LLM-powered AI applications or Retrieval Augmented Generation (RAG)/Agentic AI workflows.
Experience with microservices, Docker, Helm, Kubernetes, and software lifecycle including CI/CD pipelines.
Experienced in designing and deploying complex AI pipelines involving multi-agent systems or sophisticated workflow orchestration.
Strong understanding of LLM architectures, including tool calling, prompt engineering, structured outputs, and reasoning.
Experienced in collaborating across distributed global teams with proven ability to guide and influence technical direction in dynamic environments.