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Strong employer brand plus metro location but niche LLM platform skills reduce candidate density.
Specialized LLM platform and enterprise governance skills are moderately transferable but industry-aware.
Multiple explicit years, specific platform/LLM and security requirements create tight mandatory filters.
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Own end-to-end design and configuration of platform systems ensuring alignment with business requirements and architecture standards.
Plan and execute system deployment including compliance with hardware, software, security, and enterprise governance standards.
Identify and resolve system deficiencies while optimizing data handling, performance, and integration workflows for LLM and AI/ML platforms.
Bachelor’s degree in Computer Science, Engineering, or related technical discipline.
7+ years overall work experience with 6–8 years as Platform Engineer, AIOps Engineer, AI/ML Operations Engineer, or Automation Engineer supporting enterprise platforms.
3+ years experience with LLM platforms, embeddings, vector/graph databases, prompt management, and ingestion pipelines in production.
Experience with Git-based repositories and CI/CD pipelines (GitLab/GitHub), Linux (RHEL), automation scripting, platform security, IAM/secrets management (e.g., CyberArk, HashiCorp Vault).
Experienced technologist focused on platform engineering and AI/ML operationalization at enterprise scale, especially with LLM ecosystems.
Ability to translate business needs into technical system specifications and lead cross-functional deployment adherence to compliance and security standards.
Strong background in automation, CI/CD, and system monitoring enabling stable, scalable, and secure platform solutions.