Key Responsibilities
The role spans two connected layers, and youll move fluidly between them:
The platform. Build and maintain the shared integration and automation infrastructure layer that connects our internal systems and exposes them to AI safely – reusable connectors, reliability, security, and observability.
The solutions. Build internal tools, automations, and AI agents on top of it – integrations across enterprise SaaS (Salesforce, NetSuite, Slack, Okta), and LLM-powered workflows for things like triage, provisioning, document processing, and reporting.
The right tool for the job. Low-code/iPaaS, custom code, or a hybrid – whatever delivers value fastest and stays maintainable, with responsible-AI practices throughout.
How Youll Work
Deliver MVP-first and iterate on real usage; favor pragmatic, simplicity-first solutions over over-engineering
Own what you build end to end – design through production support – with documentation others can maintain
Communicate trade-offs clearly, and quantify the value you deliver
Scope
In scope: the internal AI-integration and automation platform and everything built on it; business infrastructure for teams across Finance, HR, GTM, Security, and IT; integration reliability and observability.
Out of scope: physical IT operations (device provisioning, inventory, AV) and endpoint/office IT support.
7+ years in integrations, business systems / MIS, or systems engineering within SaaS environments, with senior-level ownership
Hands-on experience integrating systems you dont control – their APIs (REST, GraphQL, webhooks), auth flows, rate limits, and imperfect data
Proficiency in Python and/or JavaScript (Node.js/TypeScript)
Experience with low-code/iPaaS platforms (Workato, Zapier, Make, Tray) and judgment about when to use them vs. custom code
Experience with AI-to-system integration standards (e.g., MCP)
Familiarity with enterprise systems (Okta, Salesforce, NetSuite, Google Workspace) and with IAM/OAuth, API security, and compliance (SOC 2, ISO, GDPR)
