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Generic mid-level backend title, metro location, and broad AI/backend skill requirements increase applicant competition.
Platform engineering with AI integrations is moderately transferable across industries but favors AI-platform experience.
Explicit 3+ years, mandatory Python/backend and AI API/platform experience, plus cloud and Kubernetes requirements.
Build and own the Nora AI platform components end-to-end enabling internal AI workflows.
Develop integrations to embed AI into existing operational systems like Salesforce, Jira, and internal apps.
Design and develop new AI infrastructure as needed, with focus on operational handoff and measurable business outcomes such as revenue impact or efficiency gains.
Minimum 3 years professional software development experience.
Strong backend programming skills in Python.
Proficiency with AI development stacks and APIs (e.g., Claude, Codex, OpenAI).
Experience building scalable, enterprise-grade platforms and knowledge of cloud services (AWS, GCP, Azure) plus containerization (Docker, Kubernetes).
Experienced in building and shipping platform services or SDKs used by other teams, with emphasis on sustainable API design.
Comfortable engaging with operational users to tailor AI solutions that fit real-world workflows.
Familiar with end-to-end platform ownership including documentation, defining service level objectives (SLOs), and effective product handoff to other teams.