Backend Engineer at Peppr AI (W25)
$100K - $150K  •  0.25% - 1.00%
Self-improving knowledge base synthesizing scattered company data
Cupertino, CA, US / San Francisco, CA, US
Full-time
US citizen/visa only
Any (new grads ok)
About Peppr AI

About Peppr AI

At Peppr AI, we’re building the data and intelligence layer that makes AI agents truly work inside large enterprises. AI adoption is exploding, but most orgs can't make use of agents because their data is too fragmented. Peppr solves this by learning from how employees actually work and stitching together an org-wide brain that agents can use.

We’re already deployed at enterprises with 1000+ employees like Citrix and just wrapped up the W25 Y Combinator batch. We’re a team of 4 Georgia Tech grads with 2 prior exits, and we move fast, build deep, and obsess over solving real problems.

We’re hiring another founding engineer to join us on the technical frontier — someone excited to shape the future of how humans and AI work together.

About the role
Skills: Flask, JavaScript, Python, React, Redis

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.

Technology

If you're a builder who’s excited to work on both backend systems and intuitive frontends — and want to shape how AI integrates into real-world enterprise workflows — you're a great fit.

We're looking for interns with:

  • Strong full-stack engineering skills (we work with TypeScript, React, and Python)
  • A product mindset and experience building end-to-end features
  • Fast iteration ability and comfort with ambiguity
  • Bonus: Experience with networking, authentication, enterprise security, or working with AI tooling

What You’ll Do

As an intern at Peppr AI, you’ll work across the stack to help build the infrastructure that powers the agentic AI layer for the enterprise.

You’ll be shipping real product:

  • Building frontend interfaces for how employees interact with Peppr’s AI
  • Engineering robust backend systems that process and unify organizational knowledge
  • Contributing to our internal platform that enables agents to operate securely and autonomously across fragmented enterprise tools
  • Collaborating on design, architecture, and product direction from day one

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