Senior Automation / AI Systems Engineer — Advanced Workflow & Lead Intelligence Systems

We’re looking for an experienced developer who can design and build serious multi-step automation systems, not just connect a few APIs together. The ideal person thinks at the systems level: workflows, state, orchestration, APIs, queues/events, data pipelines, AI/LLM components, retries, observability, failure recovery, cost controls, and clean integration boundaries. This is particularly suited to someone experienced with: - Python and/or TypeScript - API-heavy backend systems - Multi-step and long-running workflows - Workflow orchestration and event-driven architectures - AI/LLM and agentic workflows - Data collection, enrichment, normalization and deduplication - Lead generation / lead intelligence / sales automation - Queues, workers, webhooks and scheduled jobs - PostgreSQL or similar databases - Production reliability, idempotency and retry strategies - Designing reusable systems rather than one-off scripts Experience with tools such as Temporal, n8n, Airflow, Celery, Redis, Supabase/Postgres, scraping/data providers, enrichment APIs, LLM APIs, or similar infrastructure is useful, but we care more about engineering judgment than a specific stack. Paid Technical Assessment For strong candidates, we will offer a paid technical build. This will not be a LeetCode exercise or disposable coding test. You will be given a real-world problem around lead intelligence, aggregation, qualification and workflow automation and asked to design and implement a substantial standalone subsystem. The system should be capable of operating independently and integrating cleanly into different applications through APIs, events, webhooks or other well-designed interfaces. We intentionally will not provide an excessively detailed implementation specification. Part of the assessment is seeing: - how you decompose an ambiguous problem; - what architecture you choose; - where you use deterministic logic vs AI; - how you model workflow state; - how you handle failures and partial execution; - how you prevent duplicate or inconsistent operations; - how you design integration boundaries; - how you control external API and LLM costs; - how you make the system observable and debuggable; - and what you deliberately choose not to build. We want to see production engineering judgment, not maximum feature count. Assessment budget Approximately $400–$500 for the paid assessment, depending on agreed scope. Exceptional work can lead to substantially more development work afterward. When applying Please don't send a generic AI-generated cover letter. Instead, briefly show us one technically difficult automation/workflow system you have personally built. Explain: 1. What the system actually did. 2. What made it difficult. 3. How workflows/state were managed. 4. What could fail and how you handled those failures. 5. One architectural decision you would change if you rebuilt it today. GitHub repositories, architecture diagrams, technical write-ups, demos, or other concrete proof are strongly preferred. If your experience is primarily basic CRUD applications, simple API integrations, or no-code workflows, this probably isn't the right project. We’re specifically looking for someone who enjoys the difficult engineering underneath automation.