BackendStatus: Implemented ServiceTimeline: 2023 - 2024

Scalable REST API & Data Service

High-performance backend API with relational data modeling, RBAC, and transactional integrity

Source Code Repository✓ 90%+ unit test coverage on critical billing and authentication domain services.
TECHNOLOGY STACK
Node.jsExpress.jsTypeScriptPostgreSQLPrisma/KnexJestDocker
SYSTEM DESIGN & RUNTIME SIMULATION

Interactive Architecture & Pipeline Inspector

INTERACTIVE SYSTEM ARCHITECTURE STUDIO

Klinik Voice Intake & Triage Pipeline

Real-time stateful voice agent architecture with deterministic clinical triage routing

PATTERN: Async WebSockets + LangGraph State Machine
Sub-850ms audio-to-triage turnaround with zero hallucinated diagnoses
SYSTEM EXECUTION PIPELINE (TAP ANY NODE TO INSPECT)
STEP 0118ms

Audio Ingest Stream

Client Microphone Feed
WebSocket / 16kHz PCM
STEP 02240ms

Speech-to-Text Pipeline

Whisper Transcription Core
gRPC Streaming
STEP 03320ms

LangGraph State Machine

Clinical Decision Graph
Python / Async Graph Loop
STEP 048ms

Pydantic Schema Guard

Deterministic Validation
Zod / Pydantic V2
STEP 0565ms

EMR & Dispatch Gateway

Clinical Record Persistence
HTTPS / REST FHIR
STEP 01 OF 05WebSocket / 16kHz PCM

Audio Ingest Stream

Role: Client Microphone Feed
ARCHITECTURAL ROLE & BEHAVIOR

Captures spoken patient audio chunks in real-time over bi-directional duplex WebSockets with voice activity detection (VAD).

ESTIMATED LATENCY: 18msTRANSPORT: WebSocket / 16kHz PCM
THE CORE PROBLEM

Modern applications require secure, auditable, and performant backend services that handle concurrent requests without data race conditions or silent failures.

WHAT I BUILT & DELIVERED

Designed and developed a production-ready RESTful backend service with TypeScript, role-based access control (RBAC), robust input validation, database connection pooling, and structured error logging.

MY SPECIFIC ROLE & CONTRIBUTION

Architected database schemas, established transactional boundaries for multi-table writes, implemented rate limiting, and wrote comprehensive unit/integration test suites.

Architectural Breakdown

  • 1Layered architecture: Controllers -> Services -> Data Access Layer (Repositories)
  • 2Centralized error handling middleware mapping domain exceptions to RFC 7807 problem details
  • 3JWT-based authentication paired with token revocation blacklists in Redis
  • 4Database migration scripts and automated schema synchronization via CI pipelines

Key Engineering Decisions & Rationale

Strict validation at controller boundaries

Validating input schemas before hitting service layers prevented malformed inputs from polluting domain logic and databases.

Explicit database transactions

Ensured atomic operations for financial and multi-entity operations, guaranteeing consistency on unexpected network disconnects.

Challenges & Trade-offs

  • •Adopted strict TypeScript compiler settings (`strict: true`, `noImplicitAny: true`) which slowed initial scaffolding but prevented dozens of runtime null pointer defects.

What I Learned

  • ✓Designing clean relational foreign key constraints and indexes early pays massive dividends when query volumes grow.

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