Overview
Our client is building a governance, privacy, and AI compliance platform for regulated organizations. They already have a working MVP and are now scaling into production pilot deployments and an enterprise-ready phase. They’re looking for a full-stack engineer who can own product UI delivery (dashboards, workflows) while also contributing to platform hardening, integrations, and upcoming migrations.
What You’ll Do
Product & UI (Primary)
Build and maintain the web app: React dashboards, workflow screens, configuration/admin interfaces
Deliver high-quality UX: responsive layouts, consistent UI patterns, accessibility basics, and performance tuning
Implement interactive data experiences: charts, tables, filters, drilldowns, exports
APIs & Integrations (Core)
Integrate with REST APIs and external services: auth flows, request/response mapping, error handling, retries, timeouts
Contribute to API design patterns: consistency, pagination, versioning, idempotency, rate-limit awareness
Build/maintain integration-heavy workflows: webhooks, event-driven patterns, background processing (where applicable)
Enterprise Readiness (Strategic)
Support platform hardening: auditability, reliability, security posture, operational readiness
Contribute to data layer evolution and migration planning (e.g., Mongo DB → Postgre SQL): schema thinking, migration strategy, integrity and performance considerations
Support cloud migration readiness (AWS/Azure): environment management, secrets, deployments, observability basics
Assist with edge/security tooling where relevant (e.g., Cloudflare or equivalent)
Must-Have Skills (Non-Negotiable)
Strong React experience shipping Saa S product UI (dashboards/workflows), modern hooks patterns
Strong Java Script (ES6+) and professional engineering practices (Git, PRs, reviews)
Confident integrating REST APIs in production: auth patterns (JWT/OAuth-style), robust loading/error states, retries/timeouts, defensive programming, edge case handling
Solid UI engineering capability: componentization, responsive CSS, UI consistency and polish
Good backend fundamentals: can read/write server code, reason about data models, and collaborate on API contracts
Strongly Preferred Type Script (or strong willingness to work in a TS migration)
Experience with a modern backend runtime (Node.js/Express preferred; similar acceptable)
Data-heavy applications: charts, analytics, reporting, admin tooling
Database competence: SQL fundamentals (Postgre SQL preferred), schema/index basics, query performance awareness; familiarity with Mongo DB/document modeling concepts
State/data fetching patterns: React Query / Tan Stack Query (or equivalent)
Testing discipline: unit/integration testing (Jest/RTL; Playwright/Cypress a bonus)
CI/CD familiarity and environment separation (dev/stage/prod)
Nice to Have
Experience with No SQL → SQL migrations (Mongo → Postgres or similar)
Cloud exposure: AWS or Azure (deployments, secrets, basic networking concepts)
Observability awareness: logging/metrics/tracing and debugging production issues
Cloudflare (or similar): CDN/WAF, basic edge/security controls
Multi-tenant Saa S patterns (tenant isolation, tenancy-aware auth, data partitioning)
Docker fundamentals
Experience Level
They want someone who can operate with ownership and ambiguity. Ideal profile: 5–8+ years engineering experience (or equivalent capability). Has shipped production Saa S UI and handled integration-heavy work. Comfortable making pragmatic architecture decisions and improving an existing codebase.
What Success Looks Like (First 90 Days)
Take ownership of core UI surfaces and ship meaningful dashboard/workflow improvements
Improve API integration quality (error handling, data transformations, reliability patterns)
Contribute to an enterprise readiness plan: API consistency, security basics, operational hardening
Help shape the migration path for the data layer (Mongo DB → Postgre SQL) and cloud readiness priorities
Interview Focus Areas
React UI build quality (component structure, state management, performance, UX detail)
API integration robustness (auth, failures, retries, transformation)
Data thinking (schemas/models, dashboard logic, exports, integrity)
Practical architecture judgment (tradeoffs, maintainability, delivery speed)
Collaboration (PR hygiene, communication, documentation)
