The role
The AI Implementation Lead is the end-to-end owner of client workflow implementations on the Unburdn platform.
You'll work directly with client teams to understand how their business actually operates, find the highest-value automation opportunities, design the improved operating pattern, build and deploy the workflow, and train the people who use it.
Who you are
You're an automation expert and product-minded builder who moves comfortably between customer discovery and hands-on implementation. You may have started in software engineering before moving into product or solutions work. Your exact path matters less than the mix:
- →The customer empathy and scoping discipline of a strong product manager.
- →The stakeholder judgment to handle a client who asks for everything: decide what's real, say "not right now," and prioritize on value and effort to build.
- →The instinct to dig into why a client is asking for something and solve the root cause, not the surface request.
- →Enough technical fluency to work confidently with APIs, data, integrations, scripts, and AI systems.
- →The hands-on curiosity to prototype and build quickly with modern AI tools, including coding agents.
- →The genuine excitement of a product person who sees coding agents as an unlock: you wish there were more hours in the day to build everything you now can.
- →The judgment to choose among deterministic automation, AI agents, and human review, and to know when automation shouldn't be used.
- →The independent decision-making to own a client outcome from discovery through adoption.
- →The collaborative instinct to involve Engineering before technical risks become delivery problems.
You don't need to be a traditional software engineer. You do need to understand technical constraints, build sophisticated automations on a low-code platform, and troubleshoot what you ship.
What you'll do
- →Understand how the client actually works. Work with client teams through interviews, working sessions, and on-site engagements. Build enough trust that people show you the messy, unofficial version of the process, not only the version documented in the SOP. When a client asks for something, dig until you find the root cause behind the ask, and recognize when a process needs to be redesigned before it can be automated.
- →Find and prioritize the opportunities. Treat every workflow conversation as discovery. Separate meaningful opportunities from nice-to-haves based on value, feasibility, risk, and likelihood of adoption, and be willing to say "not right now" to the rest. Keep a sequenced roadmap for each client and bring evidence-backed recommendations to the Transformation Lead about what to automate next.
- →Design the solution. Turn an ambiguous process into a clear workflow: decide what gets automated, what stays human-owned, and where judgment or approval must remain. Design for real operating conditions (incomplete data, failures, exceptions) and for the real people adopting it. An elegant workflow that nobody uses is a failed workflow, so account for habits, incentives, and the friction of change, and validate with the people who'll use it before investing in the build.
- →Build on the Unburdn platform. Unburdn has developed a low-code AI automation platform: AI agents, script steps, integrations, triggers and schedules, human-in-the-loop approvals, and document context. You'll build complete client workflows from these blocks, use coding agents, scripts and APIs for client-specific logic, and test the happy paths, failure modes, and edge cases.
- →Launch it and make it stick. Own the workflow from prototype through production. Monitor early runs, fix what breaks, and iterate on real behavior. Train admins, process owners, and end users, and define the new operating pattern around the automation. Stay accountable for the client outcome after launch, not a successful demo.
- →Make the platform better. Know when a challenge is client-specific logic and when it reveals a reusable platform gap. Collaborate with Platform Engineering to bring the context, customer evidence, and acceptance criteria to close the gap, then finish the client build on the new capability.
Who you work with
- →Transformation Lead owns account strategy and priorities. You bring workflow reality and technical feasibility, and together you decide what matters most. Once a workflow is selected, it's yours.
- →Engineering is your team. They back you on architecture, complex integrations, troubleshooting, and new platform capabilities. You stay the client-facing owner.
- →Enablement Lead builds scalable training programs. You own the workflow-specific training for what you deliver.
- →Client Experience Coordinator handles scheduling and logistics so you stay focused on the work.
What success looks like
- →Clients feel understood: they trust you're on top of their opportunities, they can always see where the roadmap stands, and they're genuinely excited to keep building with you. High-value workflows move from discovery to reliable production use.
- →What you build solves the client's actual problem and becomes part of how they really operate, not something shelved after a demo.
- →Workflows create measurable improvements in time, quality, capacity, or risk.
- →Delivery risks and platform gaps surface early, with the evidence Platform Engineering needs to act.