AI Systems
Engineer
Build the AI that delivers our products. Agent workflows, automation pipelines, orchestration systems. Built once for Lynton, deployed again for clients.
About Lynton
Lynton spent 16 years as a HubSpot partner. 2,000+ companies, 50+ industries. We know SaaS from the inside: what it costs, how it locks companies in, where the architecture breaks down.
Two years ago, we saw what was coming. AI didn't just change the feature set. It changed the math. We left the partnership and started building what comes next. Today we help mid-market companies replace legacy SaaS with AI-native infrastructure they actually own.
The role
We sell AI-native website blueprints and sovereign stack blueprints as digital products, delivered primarily by AI. Someone has to build the AI that delivers them. That's this role.
The founder is building the first generation of autonomous AI agent teams, the delivery pipeline, and the automation frameworks right now. You inherit that foundation and make it production-grade, then extend it: new product types, deeper assessments, smarter automation, more reliable orchestration.
Build it once, ship it twice. The same AI systems you build for Lynton's internal operations get deployed for clients. The agent workflows that generate our blueprints become the agent workflows we implement for mid-market companies replacing their SaaS infrastructure.
What you'll do
- ▸Build and maintain the AI product delivery pipeline: the system that turns a client's website URL into a comprehensive technology blueprint
- ▸Create and orchestrate AI agent workflows for internal operations and client delivery
- ▸Extend existing AI-powered tools (website assessment engine, quote tool, blueprint generator)
- ▸Build the automation layer that makes Lynton's B2B ecommerce model work at scale with minimal human intervention
- ▸Design prompt architectures and agent coordination patterns that produce consistent, high-quality outputs
- ▸Integrate AI capabilities into sovereign stack deployments: intelligent CRM workflows, automated reporting, AI-assisted content operations
- ▸Monitor, evaluate, and improve AI system performance across output quality, cost, latency, and reliability
Who you are
- ●2–4 years building production systems with AI APIs (Anthropic Claude, OpenAI, or similar)
- ●Strong Node.js or Python skills. You write real applications, not notebook demos
- ●Prompt engineering beyond single-shot completions: multi-step chains, agent loops, tool use, structured outputs
- ●You've built systems that run in production with real users, not just prototypes that work in a demo
- ●Comfortable with API integrations, webhooks, and connecting multiple services into coherent workflows
- ●You think about reliability, cost, and failure modes, not just "does it work once"
- ●Comfortable with ambiguity. The field is moving fast and the playbook is being written in real-time
Bonus
- +Vector databases, RAG patterns, or document processing pipelines
- +Workflow orchestration tools or frameworks (LangChain, CrewAI, custom agent frameworks)
- +Web scraping, data extraction, or content analysis at scale
- +Familiarity with Astro, React, or modern web frameworks
Our AI stack
Anthropic Claude (Sonnet, Opus), structured outputs, tool use
Cursor, Claude Code, custom agent workflows
Custom Node.js pipelines, Cheerio for web scraping, document processing
Hetzner + Coolify (self-hosted Docker), Cloudflare CDN, PostHog
This stack is evolving. You'll have a voice in where it goes.
Why this role
- Build the engine. You're not adding AI features to someone else's product. You build the AI systems that ARE the product, then deploy them for clients.
- Ship, don't theorize. Not a research role. Every agent workflow, every automation pipeline, every prompt architecture goes into production.
- Ground floor with credibility. 16 years of enterprise relationships, a legacy client base generating revenue, and a market thesis the numbers are proving right.
- No gatekeepers. Small team. No ML platform team blocking your deployments. No six-month review cycles. You build it, it ships.
We're building
the pipeline.
This role isn't our immediate hire, but we're actively building the pipeline for when it is. If you're a strong fit, we want to know you exist before we're racing to fill the seat.
Four questions designed to surface what resumes can't. Specific answers beat polished ones. Generic AI-generated responses won't make it through.