You are a strong engineer who is excited by applied AI, not just model benchmarks.
You can build useful software quickly.
You understand LLMs, agents, retrieval, tool use, structured outputs, evals, and orchestration — but you also understand that the hard part is usually the business process, not the model call.
You are comfortable working in ambiguous environments where the requirements are messy at first.
You can talk to non-technical operators, translate what they mean, and build what they actually need.
You care about shipping systems that survive contact with the real world.
Useful Experience
- Strong experience with TypeScript, Python, or both.
- Experience building with LLM APIs such as OpenAI, Anthropic, Gemini, or similar.
- Experience with AI agent frameworks, workflow orchestration, structured outputs, retrieval, vector databases, tool calling, and evals.
- Experience integrating with third-party APIs, webhooks, databases, CRMs, internal tools, and SaaS platforms.
- Experience building internal tools, dashboards, admin panels, approval flows, or human review queues.
- Experience with cloud platforms such as Cloudflare, AWS, GCP, Azure, Supabase, or Vercel.
You’ll Be a Great Fit If
- You like turning vague business pain into working systems.
- You enjoy talking to operators and figuring out what is actually broken.
- You are not precious about tools, frameworks, or hype cycles.
- You can move fast without being reckless.
- You are comfortable building the first version, watching it break, learning why, and making it better.
- You understand that production AI requires guardrails, evals, logging, observability, permissioning, and human escalation.
- You care more about business outcomes than clever architecture.
- You would rather ship something useful than debate whether it counts as “agentic.”
You May Not Be a Fit If
- You only want to work on model research.
- You mainly want to build demos.
- You think a chatbot is the answer to every workflow problem.
- You need perfectly written requirements before you can start.
- You are uncomfortable talking directly to clients or operators.
- You are allergic to messy systems, legacy tools, spreadsheets, weird APIs, or business logic that lives in someone’s head.
This is a builder role for someone who wants to work at the edge of applied AI.
You will work directly with operators, business owners, and internal subject matter experts to understand how a company actually runs, then turn that understanding into working AI systems.
That might mean building an agent that reviews inbound requests, pulls context from multiple systems, drafts the right response, routes approvals, updates the CRM, creates follow-up tasks, and escalates exceptions to the right human.
It might also mean building the boring but critical pieces around the agent: data pipelines, tool integrations, retrieval systems, evaluation loops, human review queues, audit trails, permissions, and monitoring.
What You’ll Do
You will design and build AI agents, internal tools, workflow engines, automations, and integrations for mid-market companies.
You will work with client teams to understand real business processes, not sanitized diagrams.
You will connect AI systems to the tools companies already use: CRMs, ERPs, email, Slack, Google Workspace, Microsoft 365, databases, spreadsheets, ticketing systems, and vertical SaaS platforms.
You will build prototypes quickly, test them with real users, and turn the useful ones into production-grade systems.
You will design human-in-the-loop workflows where AI drafts, recommends, routes, summarizes, researches, classifies, or executes — but humans remain in control where judgment matters.
You will create systems that handle edge cases, bad data, missing context, permission issues, unclear ownership, and the weird “this is just how we do it” logic that exists inside every company.
How We Work
We move fast.
We get close to the business.
We ask annoying questions until the real constraint is obvious.
We prototype quickly, ship carefully, and improve based on how people actually use the system.
We believe AI implementation is not about replacing teams. It is about giving teams better systems, better leverage, and less manual drag.
$4,000-$5,000 USD per month. Competitive compensation based on experience.
Open to full-time, contract-to-hire, or exceptional fractional candidates.
How to Apply
Send us something that shows how you think and build.
That could be a project, a repo, a demo, a teardown, a technical writeup, or a short note explaining a messy workflow you would want to rebuild with AI.
We care less about credentials and more about evidence that you can ship useful AI systems in the real world.
