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Tier-1 brand and metro location attract quality applicants but role's ML/LLM specialization limits broad competition.
Role demands deep ML/LLM infrastructure and cybersecurity domain experience, limiting cross-industry transferability.
Requires specialized LLM, distributed systems, cloud-native and leadership experience, creating strict candidate filtering.
Lead architecture and delivery of scalable AI/ML infrastructure, LLM serving platforms, and agentic workflows for cloud-scale cybersecurity.
Design reusable platform foundations addressing networking, security, authentication, and monitoring for enterprise AI/ML services.
Drive cross-functional AI solution initiatives and provide technical leadership and mentorship on distributed systems design.
Experience designing and operating large-scale, low-latency distributed systems with expertise in availability, fault tolerance, consistency, and cloud-native microservices (preferably AWS).
Strong knowledge and hands-on experience with LLMs and production AI/ML infrastructure including orchestration, inference, and pipeline operations.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related technical field with solid computer science fundamentals.
Work Experience Required: Not explicitly mentioned in the JD.
Proven ability to lead architectural decisions and mentor technical teams in cross-organizational environments.
Experience building autonomous AI agentic workflows and fine-tuning domain-specific LLMs, especially for cybersecurity use cases.
Deep foundation in core systems, networking, and security architecture relevant to distributed AI systems and infrastructure.