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View current openings →About the Company
Our client is building AI software for marketing teams serving law firms and professional services clients. Their platform automates content generation, research, and multichannel publishing, with a growing emphasis on compliance for legal content. The engineering work ahead is substantive: consolidating a fragmented architecture, strengthening tenant isolation, and building the systems needed to operate AI workflows reliably in production.
About the Role
This is a senior, backend-heavy role with end-to-end ownership over the platform’s core systems. You’ll lead the migration from a Node.js/Express ECS backend to a Next.js monolith, replace N8N workflows with native async workers, and design the architecture behind AI generation pipelines, observability, billing, and publishing reliability. The role also includes a meaningful compliance dimension, from legal-content checks to auditability, alongside the multi-tenant data protections required for a production SaaS product.
What You'll Build
- Migrate a Node.js/Express ECS backend into a Next.js monolith with API routes
- Replace N8N with native BullMQ async workers for all content generation pipelines
- Implement AI observability (Langfuse or LangSmith) across Claude, Perplexity, Gemini, and
DALL-E call sites - Design and enforce Supabase RLS policies for strict tenant isolation - Build dead-letter queues, retry strategies, and alerting for async AI job failures - Implement Stripe Checkout, tier gating, webhooks, and customer portal end-to-end - Architect the compliance layer: CourtListener API integration, bar-rule checks by state, audit trail per published piece - Add per-client token cost tracking across all AI providers - Instrument WordPress REST API publishing with retry logic and per-client health monitoring
Required Experience - 5+ years full-stack engineering; 2+ years building multi-tenant SaaS - Next.js (App Router, API routes, server components) - TypeScript, Node.js, PostgreSQL / Supabase - BullMQ or equivalent async job queue architecture in production - Supabase RLS: designed and enforced tenant isolation, not just read the docs - Agentic AI systems: prompt chaining, fallback logic, output validation, non-deterministic testing - AI observability tooling (Langfuse, LangSmith, or Helicone) - Stripe billing end-to-end: Checkout, webhooks, customer portal, metered billing - OAuth integrations (Google, LinkedIn) - AWS (EC2, S3, ECS familiarity)
Nice to Have - Experience with Claude API tool use / extended thinking - Compliance or legal tech background - Prisma ORM
Not a Fit If - You treat AI API calls as just another fetch request - You've only built single-tenant apps - Observability and evals aren't part of your default workflow