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%)

📌 Backend Developer (Founding Team) (Hyderabad)
🏢 Gradientflo Labs
📍 Hyderabad