Senior Full-Stack Platform Engineer

Senior Full-Stack Platform Engineer

We're looking for a Senior Full-Stack Platform Engineer to own and evolve major parts of Mirado's internal engineering platform. This role spans full-stack application development, data systems, cloud infrastructure, partner integrations, reporting, reconciliation, and internal tools used daily by operations, sales, finance, and engineering.

You'll work across two closely related codebases: a GCP-based data warehouse and automation platform built with TypeScript services, BigQuery, and Cloud Run, and a Next.js internal web application used to manage operational workflows, merchant data, reporting, billing, launches, and partner-facing processes.

This is not a narrow feature-factory role. We are looking for someone who can understand complex systems, make sound technical tradeoffs, drive ambiguous projects from investigation through production, and improve the reliability and maintainability of the platform over time.

We work heavily with agentic coding tools such as Claude Code, Cursor, Copilot-style assistants, automated reviewers, and repository-specific AI rules. Engineering success here comes from using AI as a force multiplier while applying strong judgment: understanding the system, guiding generated code, identifying bad assumptions, debugging deeply, validating behavior, and shipping reliable changes.

You should be comfortable reading unfamiliar code, designing pragmatic solutions, building production-quality user interfaces, operating cloud systems, writing analytical SQL, and turning loosely defined operational problems into maintainable software.

What You'll Do

• Own significant portions of Mirado's internal platform, including operations tooling, reporting workflows, partner ingestion flows, merchant management, billing, reconciliation, data quality checks, alerts, and business-system integrations.
• Design and evolve full-stack platform capabilities across our Next.js internal application, TypeScript services, BigQuery warehouse, and GCP infrastructure.
• Build and improve React/Next.js interfaces that real internal teams rely on daily, including workflows, forms, tables, dialogs, dashboards, data visualizations, and operational review screens.
• Translate ambiguous business and operational problems into technical designs, implementation plans, and production-ready systems.
• Use agentic coding tools to accelerate development while carefully reviewing, testing, correcting, and validating generated code.
• Lead investigations into production issues across application code, SQL, cloud services, logs, queues, scheduled jobs, infrastructure config, authentication flows, and warehouse tables.
• Work in TypeScript monorepos with Next.js apps, shared packages, server-side APIs, validation schemas, auth/session logic, deployment scripts, and repository-specific engineering patterns.
• Write, review, and maintain BigQuery SQL for reporting, reconciliation, data quality checks, stored procedures, staging logic, source-of-truth workflows, and operational analytics.
• Operate and improve the GCP services that back these systems, including Cloud Run, BigQuery, Pub/Sub, Cloud SQL, Cloud Scheduler, Cloud Build, IAM, GCS, Secret Manager, and related deployment infrastructure.
• Integrate with partner APIs and business systems including Google Sheets/Drive, Slack, Attio, QuickBooks/Intuit, SFTP feeds, email, and other operational tools.
• Improve system observability, deployment safety, test coverage, documentation, incident response, and operational runbooks.
• Identify technical debt, reliability risks, security gaps, and data integrity issues, then drive pragmatic improvements.
• Help define engineering standards, repository guidance, AI-agent instructions, and development workflows that improve team velocity and quality.
• Participate in code review with a strong focus on correctness, production behavior, security, data integrity, maintainability, and long-term system health.

Required Qualifications

• Strong professional software engineering experience, typically 7+ years, or equivalent demonstrated expertise building and operating production systems.
• Strong computer science fundamentals, systems thinking, and practical debugging ability.
• Demonstrated ability to design and deliver production-quality full-stack systems, from database and backend services through polished user-facing interfaces.
• Strong TypeScript or JavaScript skills across application code, services, APIs, shared packages, and frontend systems.
• Experience building React user interfaces, including components, state management, hooks, forms, client/server boundaries, and user workflows.
• Solid SQL experience beyond basic CRUD, preferably in analytical warehouses such as BigQuery, Snowflake, Redshift, or similar.
• Experience operating production cloud systems, including deployment, monitoring, configuration, secrets, IAM, logging, and incident investigation.
• Familiarity with event-driven systems, queues, pub/sub messaging, scheduled jobs, asynchronous processing, and failure recovery patterns.
• Comfort working in monorepos and modern tooling such as pnpm, Turborepo, or similar.
• Ability to read and troubleshoot shell scripts, YAML, Dockerfiles, deployment config, infrastructure settings, and environment-driven systems.
• Ability to work with significant autonomy: investigating problems, asking sharp questions, making thoughtful tradeoffs, and driving work to completion without needing detailed specifications.
• Adaptability to an AI-first engineering workflow: able to review generated code critically, identify flawed assumptions, and validate behavior through tests, logs, data checks, manual inspection, and production observation.
• Strong written communication, especially for technical designs, debugging notes, operational procedures, code review, documentation, and AI-agent instructions.

Preferred Experience

• Hands-on experience with agentic tools such as Cursor, Claude Code, GitHub Copilot, OpenAI Codex-style agents, automated code review agents, AI-assisted testing, or repository rules for agent guidance.
• Next.js App Router, React Server Components, route handlers, Turbopack, React 19, and modern full-stack React application patterns.
• Frontend UI work with Tailwind CSS, component libraries such as shadcn, Base UI, or Radix-style primitives, and data visualization tools such as Recharts or similar.
• Experience building accessible, responsive internal admin UIs for operational teams.
• Strict TypeScript, Zod or similar validation libraries, typed contracts, result/error handling patterns, and shared package architecture.
• PostgreSQL, Drizzle ORM, Cloud SQL, migrations, role/capability systems, and internal business data models.
• BigQuery stored procedures, UDFs, audit tables, staging-to-source-of-truth workflows, QA queries, and parameterized analytical SQL.
• Google Cloud Run, Pub/Sub, BigQuery, Cloud Build, IAM, GCS, Secret Manager, Cloud Scheduler, Cloud Workflows, and related GCP services.
• Firebase Authentication, Google IAP, session management, authorization, entitlement systems, and internal security boundaries.
• Experience building ETL, ELT, data ingestion, billing, reporting, reconciliation, partner integration, or operational alerting systems.
• REST API integrations, OAuth2/client credentials flows, retry handling, idempotency, rate limits, backfills, and failure recovery.
• Python for data tools, scripts, notebooks, or one-off operational workflows.
• Business-system integrations such as Google Sheets/Drive, SFTP, Excel generation, Slack, Attio, QuickBooks/Intuit, transactional email, or Google Maps.
• Testing with Jest, Vitest, or similar, plus experience operating production systems: reading logs, tracing failures, validating data, responding to incidents, and improving runbooks.
• Experience mentoring other engineers, raising code quality, improving team practices, and helping shape engineering standards.

Ideal Candidate Profile

You enjoy solving problems more than typing code. You like understanding how systems fit together, how data moves, how services fail, and how to make workflows more reliable. You are comfortable moving across frontend code, backend services, SQL, infrastructure, integrations, and operational processes.

You are excited by AI-assisted development, but you do not blindly trust generated output. You know how to use AI tools to move faster while still owning the architecture, correctness, maintainability, and production behavior of the final result.

You are comfortable operating with significant autonomy. You know when to ask for input, but you do not wait for detailed specifications before making progress. You can clarify ambiguous requirements, identify hidden risks, propose practical solutions, and communicate tradeoffs clearly.

You bring strong engineering judgment, systems thinking, and a desire to leave systems better than you found them. You do not need to be an expert in every technology we use, but you should be excellent at learning from an existing codebase, validating your work, and applying sound judgment across unfamiliar terrain.

You enjoy improving the way a team builds software: better patterns, better documentation, better runbooks, better AI-agent instructions, better reviews, and more reliable delivery.