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Mid-level DevOps platform role with broad skills and metro hybrid setting increases competition.
Platform and DevOps skills transferable, but AI/LLM platform experience narrows fit to medium.
Explicit 5-8 years plus mandatory cloud, CI/CD, IaC, and enterprise controls increases strictness.
Design, build, test, deploy, and support reusable enterprise AI platform services, APIs, SDKs, and automation patterns.
Implement complex integrations with LLM services, AI gateways, orchestration frameworks, vector/search services, and enterprise identity patterns.
Build and maintain CI/CD pipelines, infrastructure-as-code, automated testing, telemetry, and operational runbooks; troubleshoot platform incidents and performance issues.
5-8 years experience building backend services, APIs, automation, cloud-native applications, or platform services.
Proficient in Python and modern software engineering practices; JavaScript/TypeScript or Java/.NET are assets.
Experience with Azure, Azure DevOps or GitHub Enterprise, CI/CD, containers, Infrastructure as Code, logging, monitoring, and secure development.
Education: University or College education in Computer Science, Engineering, Data/Analytics, Business/Technology, Risk/Governance, or related field; equivalent experience considered.
Technical expertise in backend platform development with strong operational and troubleshooting skills for AI systems.
Experience working cross-functionally with architecture, cybersecurity, data, privacy, and delivery teams to implement enterprise-grade secure and compliant AI solutions.
Familiarity with LLM application patterns and emerging AI capabilities like RAG, prompt orchestration, vector search, and AI observability enhances candidacy.