Senior Software Engineer, Full-Stack
Markup AI
About Markup AI Markup AI is pioneering the AI content governance category with the industry's first Content Guardian Agents™-AI-powered agents that automatically scan, score, and rewrite content to ensure it meets brand, compliance, terminology, and quality standards before it goes live. Purpose-built for AI-first marketing and content teams, Markup AI integrates directly into LLMs, CMS platforms, and enterprise workflows through its API- and MCP-first architecture, giving organizations the confidence to scale AI-generated content without sacrificing quality, consistency, or trust. Backed by decades of expertise in enterprise content governance, Markup AI is helping leading global brands publish faster, safer, and with confidence. Eligible candidates must reside in one of the following states: Florida, Georgia, Indiana, Massachusetts, New Jersey, New York, North Carolina, Pennsylvania, Texas About the Role We're looking for a Senior Software Engineer to own product capabilities from the data model to the final interaction. This is a frontend-leaning full-stack role: roughly 70% TypeScript and React and 30% Python and backend work, varying by project. A typical feature starts with a database query or API contract and ends as a polished experience in production. The team's scope includes organization and user management, permissions and SSO, reporting and analytics, self-serve onboarding, our shared design system, and integrations with Google Docs and Word Online through our Chrome extension. The work combines traditional enterprise product engineering with unusually difficult browser and document problems. Our product must remain dependable while AI results arrive incrementally, enterprise permission models evolve, and third-party applications change underneath our integrations. What You'll Own
- Lead substantial product features from discovery and technical design through implementation, rollout, instrumentation, and iteration.
- Build complex, responsive product experiences with React, TypeScript, Next.js, and TanStack Query.
- Design the endpoints, data models, queries, and migrations that support those experiences.
- Evolve our Chrome extension and document integrations across Google Docs, Word Online, and other enterprise authoring environments.
- Improve our shared design system while treating accessibility, keyboard behavior, and focus management as product requirements.
- Build interfaces for asynchronous and LLM-powered workflows, including streaming results, partial failures, retries, and long-running operations.
- Maintain strong automated coverage with Vitest, Testing Library, and Playwright, including end-to-end tests against third-party applications.
- Use instrumentation and evidence to diagnose production behavior, including failures caused by upstream applications we do not control.
- Write concise design documents or ADRs when a decision affects multiple systems, packages, or teams.
- Raise the engineering bar through thoughtful reviews, pairing, and improvements to shared foundations.
- Deep experience building production applications with React and TypeScript. This will often mean six or more years in professional software development, but demonstrated scope, judgment, and ownership matter more than a precise number.
- Strict TypeScript habits and clear, well-reasoned views about component boundaries, state, data flow, and API design.
- Experience with client data layers, including cache-key design, invalidation, optimistic updates, and failure recovery.
- A history of shipping features across the stack. You can explain how you designed a schema, exposed the right API, built the interface, and operated the service in production.
- Experience building enterprise software involving multi-tenancy, roles and permissions, administration, organization-level settings, onboarding, or customer reporting.
- Strong testing habits and experience treating accessibility as part of implementation rather than a later audit.
- Strong debugging abilities: working with traces, logs, product analytics, and debugging in third party applications.
- The ability to scope ambiguous work, communicate tradeoffs, and take responsibility for quality after launch.
- Building backend Python FastAPI APIs
- Streaming or SSE interfaces for AI products, including latency, partial results, retries, and non-deterministic output.
- Temporal or another distributed workflow system, including activities, determinism, retries, timeouts, and task queues.
- ClickHouse or customer-facing analytics data visualization.
Vacancy posted 2 days ago
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