AI Solutions Engineer – Agents & Automation

HeadQuarters

. Design and build AI agents and automations for external customers in the cannabis/CPG industry .

Posted 11/9/2026full-timeRemote • North MacedoniaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building AI agents and automations tailored for the cannabis and CPG industries, with strong capabilities in Python and SQL for integration and data management. Proven ability to translate customer workflows into explicit logic and deliver measurable improvements in operational efficiency.

Highest-signal resume keywords

Python ProgrammingSQL ProficiencyAI Agent DevelopmentREST API IntegrationBrowser Automation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLREST APIsBrowser AutomationGitBashModel Context ProtocolTypeScriptCloud DeploymentMulti-Tenant Architecture

Soft Skills

Operator EmpathyCustomer-Facing CommunicationDocumentation SkillsWorkflow DiscoveryTechnical Tradeoff Explanation

Tools & Technologies

Claude APIPlaywrightSalesforceHubSpotNetSuiteQuickBooksMicrosoft 365Google WorkspaceN8nZapier

Industry Keywords

Cannabis IndustryCPG IndustryAutomation EngineeringSolutions EngineeringProduction Workflows

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformJavaScriptNode.jsPythonSQLTypeScript

About the role

Key responsibilities & impact

Design and build AI agents and automations for external customers in the cannabis/CPG industry
Learn customer workflows by working with frontline staff and translate unwritten rules and exceptions into explicit logic
Assess technical feasibility and determine where agents and human review should be used
Translate customer needs into solution designs, effort estimates, scope, proofs of concept, and demos
Estimate model usage, infrastructure, and maintenance costs
Participate in customer discovery calls
Design, build, and deploy AI agents and automations for multi-step customer operations workflows
Build integrations with CRMs, ERPs, accounting platforms, email, messaging, and document storage using APIs and browser automation
Write production-quality Python for integrations, data transformation, and agent tooling
Use SQL to validate agent outputs, reconcile records, and measure accuracy
Implement error handling, retries, idempotency, logging, alerting, and graceful fallbacks
Create testing and evaluation processes, including test sets, regression checks, and accuracy tracking
Architect deployments to isolate each customer's data, credentials, and permissions
Hand off live agents to Operations Managers with runbooks, monitoring dashboards, review queues, and escalation paths
Train Operations Managers to supervise agent output and handle routine exceptions
Serve as the technical escalation point for agent failures and customer system changes
Build reusable components, templates, and deployment patterns from deployment learnings
Measure and report customer impact against baselines, including hours saved, turnaround time, error rates, and cost per run
Establish workflow baselines and deliver sustained measurable improvements
Shorten the time from signed agreement to measurable customer results
Enable Operations Managers to run agents with minimal engineering involvement
Support customer renewals and expansions through sustained results

Requirements

What you’ll need

3+ years of professional software engineering, solutions engineering, or automation engineering experience
Proof of recent production LLM workflows using Claude, OpenAI, or a similar platform that real users rely on
Strong Python skills, including structuring, testing, and debugging code
Strong SQL skills, including joins, CTEs, window functions, and data quality troubleshooting
Browser automation experience with Playwright or a similar tool
Experience with REST APIs, webhooks, OAuth, pagination, and rate limits across third-party platforms
Track record of troubleshooting production failures using logs and stack traces, isolating root causes, and implementing permanent fixes
Comfort with Bash and the command line for deployment, scheduling, and debugging
Git and version control experience
Workflow discovery skills, including interviewing process owners and translating tacit knowledge into explicit rules
Operator empathy and ability to explain technical tradeoffs in plain language
Comfort in customer-facing settings and ability to conduct technical conversations and manage scope
Strong documentation habits
Experience with the Claude API, Claude Agent SDK, or Claude Code is nice to have
Working proficiency in TypeScript / JavaScript (Node.js) is nice to have
Experience with Model Context Protocol (MCP) is nice to have
Experience building tool-using AI agents for multi-step workflows is nice to have
Prior solutions engineering, sales engineering, consulting, or agency experience is nice to have
Integration experience with Salesforce, HubSpot, NetSuite, QuickBooks, Microsoft 365, or Google Workspace is nice to have
Experience with n8n, Make, or Zapier is nice to have
Cloud deployment experience with AWS, GCP, or Azure, including containers and serverless functions, is nice to have
Multi-tenant architecture and familiarity with security reviews, SOC 2, or customer data protection requirements is nice to have
Document and data extraction from invoices, PDFs, and spreadsheets is nice to have
Background in finance, accounting, or back-office operations is nice to have
Experience working with distributed, international teams is nice to have

Benefits

Comp & perks

Work fully remotely in a collaborative environment
Build and apply AI engineering expertise by designing AI agents and automation solutions for real-world business challenges
Work directly with leading U.S. cannabis companies, helping build solutions that improve how their teams operate and scale
Grow your career through hands-on ownership, exposure to emerging AI technologies, and continuous learning