[Hiring] Automation Engineer @VSI Technologies

Role Description

You eliminate manual work. Every repetitive process a human is doing by hand across this company's commercial operations, government contracting workflows, and marketplace channels is a target for automation. You identify it, scope it, build the automation, test it against every edge case, deploy it, and monitor it. You do not build automations that require human babysitting after deployment. You build automations that run unattended and alert only when something genuinely needs human judgment. You use AI and LLMs as part of your automation stack — wherever an LLM makes the automation more capable than a rule-based system, you use it. Wherever a rule-based system is more reliable and auditable, you use that instead. You make the right technical decision for the specific task, not the most impressive-sounding one.

What You Do Every Single Day

• Identify automation opportunities across every department proactively — you do not wait for a request.
• Analyze workflows, identify manual steps, calculate time cost, and propose automations with a documented ROI estimate.
• Build no-code and low-code automations using Make.com, Zapier, or n8n.
• Build coded automations in Python when the task requires custom logic, complex data transformation, or performance that no-code tools cannot deliver.
• Integrate LLMs into automation workflows for document processing, data extraction, classification, content generation, and routing decisions.
• Build government contracting automations — SAM.gov monitoring, opportunity scoring, proposal section routing, compliance checklist generation, pricing data extraction from USASpending.gov.
• Build marketplace automations — Amazon listing updates, inventory alerts, pricing rule enforcement, sales data aggregation across Shopify and Walmart, order routing.
• Build AI-powered document processing pipelines — intake an RFP, extract all requirements, classify by section, map to capabilities, output a structured brief without human intervention.
• Test every automation against edge cases before deployment.
• Monitor all deployed automations — you know which ran last night, which failed, and which produced outputs needing human review before anyone tells you.
• Document every automation — inputs, outputs, triggers, failure handling, dependencies, and how to disable it if something goes wrong.
• Submit a written daily standup update every working day without exception.

Qualifications

• Minimum 4 years of professional experience building production automations using Make.com, Zapier, n8n, or equivalent.
• At least 2 years must be complex multi-step workflows with conditional branching, error handling, retry logic, and data transformation running unattended in production.
• Minimum 3 years of professional Python for automation, data processing, and API integration.
• Minimum 4 years of professional experience consuming REST APIs across a wide variety of enterprise platforms.
• Minimum 2 years of professional experience integrating LLM APIs into automated production workflows.
• Minimum 3 years of professional experience transforming and routing data between systems.
• Minimum 3 years of building and maintaining monitoring systems for production automations.
• Minimum 2 years of building automations handling regulated data — CUI, PII, HIPAA, or equivalent.

Requirements

• 3–5 years of professional automation and integration experience with at least 2 years of complex production automations running unattended.
• You have integrated an LLM into an automation workflow — not a chatbot, an automated pipeline.
• You have used Make.com, Zapier, n8n, or equivalent at a professional level.
• You can write Python well enough to build a data processing script, call an API, handle exceptions, and log activity.
• PST Time Zone.
• Professional written English — documentation, daily updates, and task communication are clear and complete.
• If an automation fails at night, you have identified it and started the fix before anyone asks.