AI Solutions Engineer - Agents & Automation
H
HeadQuartersCannabis / CPG
Serbia. MexicoFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 3+ years of professional software engineering, solutions engineering, or automation engineering experience
- Required Skills
- PythonSQLBashGitOAuthRESTful APIsPlaywright
Requirements
- Have 3+ years of professional software engineering, solutions engineering, or automation engineering experience.
- Provide evidence of recent production LLM workflows built with Claude, OpenAI, or a similar platform that real users rely on.
- Use Python to structure, test, and debug code, and understand AI-generated code before shipping it.
- Have strong SQL skills, including joins, CTEs, window functions, and data quality troubleshooting.
- Have browser automation experience with Playwright or a similar tool.
- Have experience with REST APIs, webhooks, OAuth, pagination, and rate limits across third-party platforms.
- Have a track record of troubleshooting production failures by reading logs and stack traces, isolating root causes, and fixing them.
- Be comfortable using Bash and the command line for deployment, scheduling, and debugging.
- Use Git and version control as a standard part of your work.
- Be able to interview workflow operators, uncover unstated steps and exceptions, and turn tacit knowledge into explicit rules.
- Build trust with frontline staff and explain technical tradeoffs in plain language.
- Be comfortable leading technical customer conversations and pushing back on scope when needed.
- Maintain strong documentation habits for non-engineering users.
Responsibilities
- Learn customer workflows from frontline staff and translate rules and exceptions into explicit logic.
- Assess technical feasibility, identify suitable agent tasks, and determine where human review should remain in the loop.
- Translate customer needs into solution designs, effort estimates, and clear scope.
- Build proofs of concept and demos, and estimate build and run costs.
- Design, build, and deploy AI agents and automations for multi-step customer workflows.
- Integrate customer tools using APIs where available and browser automation where they are not.
- Build error handling, retries, idempotency, logging, alerting, and fallbacks into production systems.
- Create testing and evaluation processes, including test sets, regression checks, and accuracy tracking.
- Isolate each customer's data, credentials, and permissions in deployment architectures.
- Hand off live agents to Operations Managers with runbooks, monitoring dashboards, review queues, and escalation paths.
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