Pearl Talent - Code-based Automation Engineer
We're hiring an Automation Engineer for Pearl, which finds exceptional talent from around the world, trains them to be AI-native, and places them into operational roles at startups as managed contractors: from client-facing roles to software engineers to executive assistants. We're 3x founders who've bootstrapped our company to a couple million in ARR and are adding six to seven figures in net new annualized revenue each month. Our clients span venture-backed tech and healthcare, including fast-growing startups and phenomenal US-based businesses that have raised over $3B in funding from Sequoia, a16z, Founders Fund, Y Combinator, and other top VC firms.
Today we're roughly 50 people managing a few hundred talents, growing fast and into new verticals. We started Pearl because we believe that even though opportunity isn't created equal in the world, ambitious talent is. And our goal is to scale Pearl to $100M in ARR bootstrapped by placing 2777 operators into top startups in the next 3 years.
Location: Remote-first, with meaningful overlap with US business hours
Purpose of Your Role
Pearl runs on automation. Candidate profiling, CRM hygiene, client reporting, talent operations — a meaningful share of the business moves through n8n, Zapier, and a long tail of low-code glue. That got us here, and it will not get us to $100M.
Your job is to move Pearl's business-critical workflows off no-code and onto a code-first foundation: version-controlled services, durable orchestration, real observability, and recovery paths that don't depend on someone noticing a workflow went red. You'll be handed automations that work until they don't, and you'll return infrastructure that can be tested, monitored, and safely operated by an engineering team.
This is not a "wire up another Zap" role. You're rebuilding the operating substrate of the company.
What You'll Own
- Migration from No-Code to Code
- Own the transition of business-critical automations off n8n, Zapier, and similar platforms into maintainable software services
- Reverse-engineer triggers, steps, dependencies, business rules, retries, and the edge cases nobody documented
- Sequence migrations by business criticality, reliability risk, and maintenance burden — not by what's easiest to lift
- Validate migrated behavior against production before anything legacy gets deprecated, with a clear rollback path every time
- Durable Orchestration and Integrations
- Build long-running, failure-resistant workflows in Temporal.io or a comparable orchestration framework
- Design for the real world: API outages, worker restarts, rate limits, partial failures, and processes that run for days
- Implement retries, timeouts, idempotency, checkpoints, and state management; keep orchestration separate from business logic
- Build and maintain integrations across our CRM/recruiting stack, Supabase/PostgreSQL, Google Sheets, Slack, and internal APIs — as reusable connectors, not one-offs
- Reliability, Observability, and Data Integrity
- Make failures visible, diagnosable, and recoverable instead of silent
- Ship structured logging, monitoring, alerting, and execution visibility; build clear mechanisms to replay and recover stuck jobs
- Prevent duplicate processing through idempotent operations and explicit execution boundaries
- Build reconciliation and audit trails where they matter, and respect source-of-truth and ownership boundaries across production systems
- Engineering Standards
- Write clean, documented, well-tested Python and/or TypeScript, shipped through Git, code review, automated testing, and CI/CD
- Document architecture, dependencies, assumptions, and recovery procedures so the next person isn't reverse-engineering you
- Help define the reliability standards the rest of our automation infrastructure gets held to
Example Projects
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n8n to Temporal migration: rebuild a multi-step operational workflow as a durable Temporal workflow with retries, recovery, and f