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Mid-level, metro location and broad skill set increase applicant competition.
Platform and cloud skills transfer across industries, but AI/LLM specialization increases domain specificity.
Explicit 1-5 years plus mandatory cloud, CI/CD, and platform skills create strict shortlisting filters.
Design, build, test, deploy, and support reusable AI platform capabilities including services, APIs, SDKs, and automation patterns.
Implement and maintain integrations with LLM services, AI gateways, orchestration frameworks, vector/search services, and enterprise identity patterns.
Manage platform CI/CD, infrastructure-as-code, automated testing, telemetry, operational runbooks, and ensure compliance with architecture, cybersecurity, and privacy standards.
1-5 years of experience building backend services, APIs, automation, cloud-native applications, or platform services.
Proficiency in Python and modern software engineering practices; JavaScript/TypeScript or Java/.NET is a plus.
Experience with Azure, Azure DevOps or GitHub Enterprise, CI/CD pipelines, containers, Infrastructure as Code, logging, monitoring, and secure development practices.
University/College education in relevant fields (CS, Engineering, Data/Analytics, Business/Technology, Risk/Governance) or equivalent experience.
Has experience working with AI platform technologies including LLM application patterns, retrieval augmented generation, prompt orchestration, vector search, and AI observability.
Operates effectively in cross-functional teams involving architecture, cybersecurity, data, privacy, and solution delivery to ensure robust platform capabilities.
Capable of handling production incident troubleshooting, operational support, and developing developer enablement documentation for platform adoption.