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Backend Engineer

Peppr AI · Cupertino, CA, US / San Francisco, CA, US

$100k - $150k
On-site
Full-time
Mid
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Job Description

What You'll Do As a founding backend engineer at Peppr AI, you'll architect and build the robust infrastructure that powers our agentic AI platform. You'll design PostgreSQL-based systems, implement secure authentication layers, manage cloud deployment pipelines, and help build the foundational systems that let AI agents interface securely with enterprise data.

Key responsibilities include:

  • Design and maintain reliable PostgreSQL schemas, indexes, migrations, and backups
  • Build secure auth layers: authentication, fine-grained authorization, and RBAC systems
  • Containerize and deploy services on Kubernetes (or similar), integrating with CI/CD tooling
  • Monitor production performance, latency, reliability, and security across all systems
  • Collaborate on frontend integration and infrastructure improvements
  • Bonus: Help architect and build AI agent pipelines and orchestration systems

What We're Looking For We're seeking a builder who can create scalable, secure backend systems that form the foundation for AI-powered enterprise tools. You should have:

Required:

  • 3+ years in backend development with strong PostgreSQL experience
  • Solid grounding in cloud platforms: AWS/GCP/Azure, Docker, and Kubernetes
  • Strong security awareness: authentication, authorization, and encryption best practices
  • Familiarity with API frameworks (FastAPI, Flask, Django)
  • Excellent collaboration and code review habits with a strong team mindset

Nice-to-Have:

  • Hands-on experience with AI-centric pipelines, vector stores, and agent orchestration (RAG, LangChain, etc.)
  • Experience with cloud infrastructure tools: Terraform, Helm, GitOps
  • Background in production-grade security architectures (RBAC, IAM policies)
  • A product mindset and experience shipping end-to-end features
  • Comfort with ambiguity and rapid iteration in a startup environment

This role offers the opportunity to shape both our technical architecture and product direction while working on cutting-edge AI infrastructure challenges.

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