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Mid-level, generalist platform role with popular title and moderate brand attracts moderate applicant density.
Platform engineering skills transfer across industries, but AI/LLM and enterprise controls increase domain specificity.
Explicit 1-5 years plus mandatory cloud, Python, CI/CD, containers and IaC skills increases filter strictness.
Design, build, deploy, and maintain reusable AI platform services, APIs, SDKs, and automation patterns for enterprise-wide usage.
Integrate AI platform with LLM services, AI gateways, orchestration frameworks, vector/search services, and enterprise identity patterns ensuring operational stability and security.
Support CI/CD pipelines, infrastructure-as-code, automated testing, telemetry, and troubleshoot platform incidents across development and test environments.
1-5 years experience in backend services, APIs, automation, cloud-native or platform services development.
Proficiency in Python and modern software engineering practices; JavaScript/TypeScript or Java/.NET is a plus.
Experience with Azure ecosystem (Azure DevOps or GitHub Enterprise), CI/CD, containers, infrastructure-as-code, logging, monitoring, and secure development.
Education in Computer Science, Engineering, Data/Analytics, Business/Technology, Risk/Governance or equivalent experience.
Experienced in delivering backend platform components within cloud-native environments with emphasis on automation and operational support.
Familiar with AI development patterns including LLM application, retrieval augmented generation (RAG), prompt orchestration, vector search, model evaluation, and AI observability.
Works effectively with cross-functional teams including architecture, cybersecurity, data, and solution delivery to meet enterprise security and operational controls.