Full-Stack Lead (Backend/Infrastructure)

Location: Remote

Type: Contract or Full-Time

Start Date: ASAP

The Role:

You'll be a founding backend engineer responsible for architecting and owning the core platform powering the predictive intelligence system. This includes authentication, metering, AI pipeline orchestration, and billing. You'll work directly with leadership and influence every major technical decision.

What You'll Own:

- Authentication & Identity: Firebase Auth, SSO foundations, tenant/user modeling, tier-based feature gating

- RCA Engine: Vertex AI/Gemini integration, prompt engineering, structured response parsing, high-performance request routing

- Storage & Data Layer: Redis for ephemeral RCA storage, BigQuery/Iceberg for persistent data, Cloud SQL + pgvector for embeddings

- Quota & Usage Management: Monthly RCA limits, trial tracking, enforcement logic, upgrade triggers

- Billing & Subscriptions: Stripe integration, webhooks, lifecycle automation, tier transitions

- Observability & Reliability: Logging, metrics, tracing, error tracking, audit logs, health checks

You Should Have

Required:

- 4+ years backend engineering experience (Python or Node.js preferred)

- Production RESTful API experience

- Hands-on GCP services experience (Cloud Run, BigQuery, Cloud SQL, or equivalents)

- LLM API integration and tuning experience (Vertex AI, OpenAI, Anthropic, etc.)

- Stripe (or similar) billing/subscription integration experience

- End-to-end system ownership in fast-moving teams

- Strong debugging, performance tuning, and reliability engineering fundamentals

Nice to Have:

- Firebase Authentication (or equivalent identity platforms)

- Redis for caching or ephemeral data

- Apache Iceberg, data lakes, or multi-tier storage design

- Freemium/tiered SaaS product experience

Why Join

You'll influence core platform architecture, build systems that launch immediately, and work in an early-stage environment where individual engineering decisions define the company's technical direction and scalability.