Join Sitetracker's Operations team and play a pivotal role in shaping our AI-first future, directly enabling our customer-facing teams across the business. This is a unique opportunity to build, test, and deploy AI agents and automations from the ground up, replacing manual processes and dramatically increasing the velocity and efficiency of critical business functions. You'll be at the forefront of structuring our team around cutting-edge AI, not just layering it on top, seeing the direct business impact of every solution you create.
As an Operations Associate - AI Developer, you will step into a brand-new role designed to leverage your expertise with leading AI tools like Claude, Agentforce, Cursor, and Gemini, alongside agent frameworks, to construct intelligent automations that live inside and interact with Salesforce. This includes building Salesforce Flows, Apex backed automations, LWC components, and AI powered actions that read and write to Salesforce objects, surfacing insights, triggering workflows, and eliminating manual work across our Customer Experience organization.
This role operates on an afternoon shift to ensure meaningful overlap with the US-based Director of Operations and the broader Customer Experience team. For candidates based in Mexico City, this means approximately 8:00 AM – 5:00 PM CST. The majority of design document handoffs, build reviews, and quality gate discussions happen during the overlap window with EST time.
You will receive clear, structured design requirements and user stories from the Director of Operations and independently translate these briefs into fully functional AI agents, automations, and skills. This role is part of a dynamic, shared builder pool, requiring you to demonstrate cross-domain capability, seamlessly executing builds across both process automation and Salesforce systems domains to deliver high-impact solutions for our global operations.
You will execute a complete build cycle for every assignment: read and clarify the design document and user stories before starting, build independently, self-test against defined acceptance criteria, and submit a fully documented build — including test data and expected outputs — for quality review. Builds that pass the quality gate go to production. Builds that do not come back with a clear failure report, and you address them before
Build multiple AI-assisted automations or agents in a professional context.
Describe your design-to-build process, including how you test outputs and articulate end-user interaction.
Write or review effective prompt engineering logic, explaining how specific structures optimize outputs.
Define and execute AI agent quality testing, including regression checks and documenting expected vs. actual outputs.
Deploy AI agents or automations in a production environment, defining scope, writing prompts, validating outputs, and documenting for handoff.
Configure complex Salesforce Flows, validation rules, or automation in a professional context.
Understand Salesforce object relationships, APIs, and data management.
Read and interpret basic Apex or SOQL to understand existing code or automation.
Build Salesforce automations that connect to external systems or trigger cross-object workflows.
Troubleshoot complex configuration/code issues, manage permissions, and build multi-step conditional automations (declarative or programmatic).
Translate structured written designs and user stories into working builds with minimal iteration.
Self-test builds against acceptance criteria before submission.
Submit complete, well-documented builds with test data and expected outputs for QA review.
Define your own testing protocol for builds, including inputs, expected outcomes, and pass/fail criteria.
Deliver technical builds or configurations from written designs with a high first-pass acceptance rate, consistently describing your testing and documentation process.
Demonstrate active engagement with AI tools through built projects, published work, or professional application.
Proactively learn new AI tools or frameworks outside of formal training programs.
Introduce new AI tools or approaches to a team or project, describing the resulting impact.
Maintain a documented project history showcasing progressive AI and automation skill development.
Actively track developments in the AI and automation space, building personal projects or contributing to open-source AI automation, and articulating trade-offs between different AI tools.
