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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