About the role
Our Revenue Operations team has already begun experimenting with AI agents and automation across the go-to-market lifecycle. We’ve seen enough to know there is a much bigger opportunity.
Now we’re looking for an AI builder to take that from experimentation to a real capability across the Go To Market teams at Buildots.
You’ll identify high-value opportunities, build and deploy AI-powered workflows and agents, create the foundations that allow them to operate safely in production, and help define how AI becomes part of the everyday operating model for our GTM organization.
This is a hands-on builder role with broad ownership. You’ll work across Sales, Solutions, Customer Success, Marketing and RevOps, combining engineering ability with a strong understanding of how commercial organizations actually work.
What you'll do
Build AI into the GTM lifecycle- Design and ship agents, automations and AI-powered workflows across areas such as prospecting and enrichment, lead management, account planning, deal support, approvals, pipeline management, forecasting, call intelligence and expansion.
Turn prototypes into production systems- Take promising internal experiments and build them into reliable services that can be used across the organization. You’ll work with our engineering and DevOps teams to make sure what we build is secure, maintainable and scalable.
Design for trust and appropriate autonomy- Define where AI can act independently, where people should remain in the loop, and how those boundaries are enforced. You’ll build the evaluation, monitoring, permissions and audibility needed for agents that interact with real commercial systems and data.
Build on strong data foundations- Agents are only as useful as the systems and data they can rely on. You’ll work across our CRM, GTM tools and data warehouse to improve how information is connected, structured and made available to AI-powered workflows.
Measure real business impact- We care less about the number of agents shipped than what they change. You’ll measure impact through outcomes such as faster cycle times, better data quality, higher productivity, improved conversion or time returned to teams — and communicate that impact clearly to the business.
Make the whole organization more capable- You won’t be the only person building with AI. Part of your role is creating the patterns, tooling and standards that allow others to build safely and effectively — while making it easy for the wider organization to discover, trust and use what has been created.
Requirements:
3-7 years of relevant experience, in roles such as GTM Engineer, AI GTM Engineer, RevOps Engineer, Business Applications Engineer, a Solutions/Sales Engineer with a strong technical background, an AI-forward Salesforce Developer, or a Forward Deployed Engineer.
Strong engineering ability. You can take an idea from prototype to working production system, integrate with APIs and existing applications, and make pragmatic technical decisions along the way.
Hands-on experience building with LLMs and agents. You’ve built systems involving tool use, structured workflows, context management, retrieval, agent frameworks or similar approaches, and understand how to evaluate whether they are actually working reliably.
Production mindset. You’re comfortable deploying and operating cloud-based services and working with concepts such as authentication, permissions, CI/CD, secrets, monitoring and observability.
Integration experience. You’re comfortable working with REST APIs, webhooks, OAuth, Slack applications, SQL and data warehouses.
Good judgment about AI autonomy. You understand the difference between generating an answer and taking an action, and know how to design systems appropriately when AI interacts with important business processes.
Commercial curiosity. You naturally look for high-leverage problems. You can understand a workflow, determine whether it is worth automating, and connect what you build to a measurable business outcome.
The ability to bring people with you. You can explain technical choices clearly, work across functions and build confidence in new ways of working.
You don’t need to have used every technology in our stack or already know the answer to every architectural question. We care much more about whether you have built real things, learn quickly and can make good decisions in an environment where the playbook is still being written.
Why join us?
You’ll be joining at the point where AI inside Buildots is moving from individual experimentation to organizational capability.
There is executive backing, a strong pipeline of opportunities and teams that already want to use what you build — but there is no fixed blueprint for how it should all work.
You’ll have the opportunity to define that blueprint: what we build, how we build it, where AI should act autonomously, how we measure its impact and ultimately how an AI-native GTM organization operates.
If that sounds like an interesting problem to own, we’d love to talk.
Requirements
