Back
Tier-1 Cisco brand but niche Agentic AI/LLM specialization reduces applicant density.
Specialized LLM and Agentic AI production skills limit cross-industry transferability.
Explicit 5–10 years plus mandatory LLM, LangGraph, Python, cloud and production requirements.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead design and development of scalable Python backend systems, data pipelines, and Agentic AI/LLM systems using LangGraph.
Define and drive architecture for AI/RAG systems, cloud-native infrastructure on AWS (S3, SQS, SNS, Lambda, Docker, Kubernetes), focusing on LLM performance and cost optimization.
Mentor engineers, resolve complex technical and production issues, and align technical strategy with business goals through stakeholder collaboration.
5 to 10 years of hands-on experience in machine learning engineering, backend development, and applied AI.
Deep expertise in Agentic AI, LLM applications, LangGraph, RAG architectures, and operationalizing deep learning/LLM models in production.
Strong Python backend engineering skills and experience with distributed systems and cloud-native architecture (AWS components like S3, Lambda, Kubernetes).
Experience optimizing LLM systems for token use, latency, throughput, cost, plus ETL optimization; familiarity with LLM evaluation tools like LangSmith.
Experienced in leading complex AI/cloud software architecture and multi-agent system deployments with version control and runtime safeguards.
Able to mentor teams, lead cross-functional technical initiatives, and translate business goals into scalable AI and backend solutions.
Strategic thinker with knowledge of network technologies, enterprise platform integration, and strong technical communication skills including executive-level storytelling.