Backend Developer (Founding Team)

Role Overview

You will own Vibecoderz’ engine room. Every interaction the TutorAgent orchestrates, every artifact generated, every certification issued — it all runs through your services. From Firestore schemas to FastAPI microservices and background workflows, you’ll design and build the backbone that powers _Superficient Learning_ for developers worldwide.

This role goes beyond writing APIs — you will define system contracts, data models, and scalability patterns that allow Vibecoderz to serve 100K+ concurrent learners with sub-100ms latency. You’ll work in lockstep with FE, AI, Prompt, and DevOps to ensure the platform’s foundation is secure, performant, and future-proof.

You’ll use Linear for sprints, Notion for PRDs, and GitHub for repos , collaborating across the team to make backend decisions visible, reproducible, and accountable.

Key Responsibilities

1. Service Architecture & APIs - Design, build, and maintain FastAPI microservices with clean modular boundaries.

2. Data Modeling & Schemas - Define Firestore schemas for users, courses, artifacts, results, and certifications. Manage Neo4j Developer Graph integration.

3. Asynchronous Workflows - Implement Cloud Tasks + Cloud Workflows for long-running jobs (certificate generation, artifact rendering, learner graph updates).

4. Commercial Layer - Integrate Stripe (subscriptions) and SendGrid (transactional email) via Firebase extensions. Ensure compliance with billing and audit standards.

5. Performance & Scale - Optimize services for high throughput with async I/O. Achieve <100ms API response time under load.

6. API Gateway & Security - Expose services through GCP API Gateway with JWT verification, rate limiting, and role-based access.

7. CI/CD Pipelines - Collaborate with DevOps to maintain GitHub Actions pipelines for automated testing, containerization, and deployment to Cloud Run.

8. Testing & Reliability - Write integration tests, contract tests, and load tests. Ensure regression-free releases.

9. Monitoring & Observability - Instrument services with OpenTelemetry for distributed tracing, logging, and metrics. Ensure failures are detectable and recoverable.

10. Cross-Team Collaboration - Work closely with PM to refine PRDs in Notion, track sprint execution in Linear, and align with AI/FE on contract stability.

11. Problem Solving - Anticipate bottlenecks (data modeling, latency, scaling) and propose architectural solutions.

Success Metrics

90 Days (Probation):

• Deploy FastAPI → Cloud Run service with API Gateway routing.
• Ship Firestore schema for Developer Graph (MVP).
• Integrate Stripe test billing and SendGrid notifications.

12 Months:

• Scale backend to handle 100K+ concurrent learners.
• Maintain 99.9% uptime with zero Sev1 backend-originated outages.
• Optimize p95 API response time <100ms under production load.
• CI/CD coverage >90% with automated regression tests.

Must-Haves

• 10+ years backend engineering experience (Python, REST/async).
• Deep expertise in distributed systems, scalable APIs, and async I/O.
• Hands-on GCP experience (Cloud Run, Firestore, Pub/Sub, API Gateway).
• Proven delivery of high-scale backend systems in product companies.

Nice-to-Haves

• Experience with Neo4j Graph DB.
• Prior work on AI product integrations (LLM orchestration, eval pipelines).
• Knowledge of Pub/Sub patterns for agentic systems.
• Startup or founding engineer background.

Tech Stack Visibility

• Core Services: FastAPI, Python Async, Google Cloud Run
• Routing & Security: Google Cloud API Gateway, Firebase Auth
• Data: Firestore, Neo4j Aura (Developer Graph), Redis
• Workflows: Cloud Tasks, Cloud Workflows
• Commercial: Stripe (Firebase Extension), SendGrid (Firebase Extension)
• CI/CD: GitHub Actions, Docker
• Observability: OpenTelemetry, Google Cloud Trace
• Tools: Linear (execution), Notion (PRDs), GitHub (repos)

Assessment

Objective: Validate ability to build scalable FastAPI backend services with async workflows and integrations.

Challenge (Candidate PoC):

Build a FastAPI backend powering an AI Tutor mock system with:

1. /generate-course endpoint → Input: “Teach me React Hooks.” Output: structured course outline (JSON).

2. /generate-artifact endpoint → Generates quiz or slide deck JSON artifact.

3. /generate-miniapp endpoint → Returns runnable JS snippet.

4. Store all results in Firestore (schemas for userId, courseId, artifactId).

5. Trigger Cloud Task for certificate generation (mock PDF).

6. Fire Firestore trigger → Send transactional email via SendGrid extension.

7. Secure endpoints with Firebase JWT verification through API Gateway.

Deliverables:

• FastAPI app deployed on Cloud Run.
• Firestore schema + example populated data.
• Postman collection for API requests.
• GitHub repo with modular code + CI pipeline.
• Short Loom walkthrough demo.

Evaluation Criteria:

• Service Architecture & Code Quality (30%)
• Data Modeling & Schema Design (20%)
• Async Workflow & Cloud Task Integration (20%)
• API Security & Performance (15%)
• Documentation & Testing (15%)