SoFi·Software Engineer·Onsite - System Design / Architecture·Senior

SeniorPrefer not to say

May 2026

Summary

System design round at SoFi for a software engineer role. The whole thing was one big open-ended question about building a random number generation service, and it went in way more directions than I expected.

Questions Asked (1)

Design a large-scale service that exposes both REST and streaming endpoints for generating random numbers. Walk through the API contracts and versioning strategy, your choice of entropy sources and whether you'd use a cryptographically secure PRNG or a standard one, how seeding and reproducibility work, rate limiting and quotas, multi-tenant isolation, security and abuse prevention, observability, deployment and scaling, and your SLA targets for latency and availability.

System DesignTechnical Trade-offsAPI & Integrations

Author's notes

This was basically a whole system design interview packed into one question.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then design the API contracts and versioning strategy before diving into the internals. Structure your answer around the key areas: API design, entropy/PRNG choices, multi-tenancy, security, observability, scaling, and SLAs. Emphasize trade-offs and justify decisions based on the use case (e.g., cryptographic vs. standard PRNG).

Pro tip: Demonstrate awareness of SoFi's regulated fintech environment by prioritizing security, compliance, and auditability in your design. Mention that you would separate the control plane (API management, quotas) from the data plane (number generation) for scalability and isolation.

1. Clarify Requirements and Constraints

Ask questions to understand expected throughput, latency, security needs, and whether numbers must be cryptographically secure. Identify if reproducibility is required for testing or auditing.

2. Design API Contracts and Versioning

Define REST endpoints (e.g., GET /v1/random?min=1&max=100&count=10) and streaming endpoints (e.g., WebSocket or SSE). Use URL versioning (e.g., /v1/) and include version in streaming handshake. Specify response formats, error codes, and idempotency.

3. Choose Entropy Sources and PRNG

For cryptographic security, use a CSPRNG seeded from a hardware entropy source (e.g., /dev/urandom, AWS KMS). For non-security use, a standard PRNG like Mersenne Twister with a seed for reproducibility. Explain when to use each.

4. Address Multi-Tenancy, Security, and Abuse Prevention

Implement API keys or OAuth for authentication, per-tenant rate limiting and quotas using a token bucket or sliding window. Isolate tenants via separate namespaces or resource pools. Add DDoS protection, input validation, and audit logging.

5. Plan Observability, Deployment, and SLAs

Instrument with metrics (latency, error rates, throughput), logging, and tracing. Deploy stateless services behind a load balancer, auto-scale based on load, and use a CDN for static content. Define SLAs: e.g., 99.99% availability, p99 latency < 100ms for REST, < 200ms for streaming.

Key Points to Mention

API versioning strategy: URL path versioning (e.g., /v1/) and deprecation policy with sunset headers.
Choice of PRNG: CSPRNG (e.g., AES-CTR DRBG) for security-critical use, standard PRNG (e.g., xorshift) for high-throughput non-security use.
Seeding and reproducibility: Allow clients to provide a seed for deterministic sequences, but ensure seeds are not reused across tenants to prevent predictability.
Rate limiting and quotas: Use a distributed rate limiter (e.g., Redis) with per-tenant limits, and return 429 with Retry-After header.
Multi-tenant isolation: Enforce tenant-specific encryption keys, separate queues, and resource quotas to prevent noisy neighbor issues.
Observability: Expose Prometheus metrics, structured logs, and distributed traces; set up alerts for SLA violations.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.