AI Automation Engineer (Junior to Mid-Level) | Fully Remote

Full-time | 40 hours per week | USA-based client | PST time zone

We are currently recruiting for an AI Automation Engineer to join an established technical team building practical AI-powered automations and workflows.

This is a hands-on, build-focused role suited to an early-career to mid-level engineer who has already experimented with or built AI/LLM applications and wants to develop those skills into reliable, production-ready solutions.

You will work alongside an established AI and technical team, with guidance, code review and architectural support as you take on increasingly complex projects.

The Opportunity

As an AI Automation Engineer, you will help build, test, deploy and improve AI agents and LLM-powered workflows based on defined business requirements.

You will work across:

• Building and maintaining AI agents and LLM-based automations from defined requirements
• Working with modern LLM platforms and APIs such as OpenAI, Anthropic and similar providers
• Using automation and orchestration tools such as n8n, Make, Zapier, LangChain, LangGraph or similar
• Connecting AI workflows to APIs, databases, SaaS platforms and business systems
• Translating business requirements into practical, working AI workflows
• Identifying business processes that may be suitable for AI automation
• Testing and troubleshooting AI workflows and agent behaviour
• Monitoring deployed automations for reliability, accuracy and cost efficiency
• Improving prompts, workflows, tool use and agent performance based on testing and results
• Supporting the evaluation of new AI tools, frameworks and models
• Following established security, privacy and data-handling practices
• Working with senior AI and technical team members to deploy solutions responsibly
• Documenting workflows, integrations, data flows and technical decisions clearly

What We're Looking For

The most important requirement is genuine hands-on experience.

Professional production experience is helpful, but it is not essential. Strong personal, freelance, academic or side projects are welcome, provided you can clearly demonstrate what you personally built and explain how it works.

You should have:

• Approximately 1–4 years of software, automation or technical experience, or equivalent demonstrated capability
• Demonstrable experience building AI agents, LLM applications or AI-powered automations
• Working experience with LLM APIs and prompt design
• Experience with at least one AI agent, automation or orchestration framework
• Working programming ability in Python or JavaScript/TypeScript
• Ability to build and troubleshoot API integrations and automation workflows
• Understanding of REST APIs, JSON and basic software development concepts
• Basic understanding of AI security and privacy principles, including safe credential handling and protection of sensitive data
• Strong problem-solving and debugging skills
• Strong written communication and documentation skills
• Ability to work independently while taking direction and feedback from senior engineers
• Ability to work remotely with US-based stakeholders and align with PST working hours
• A proactive and curious approach to learning new AI technologies

Nice to Have

• Experience with LangGraph, LangChain, CrewAI, AutoGen or similar frameworks
• Experience with MCP (Model Context Protocol)
• Experience with Playwright, Selenium or browser automation
• Exposure to RPA, computer-use agents or activity-monitoring technologies
• Experience integrating AI with CRM, ticketing, productivity or other SaaS platforms
• Experience with Docker or cloud platforms such as AWS
• Familiarity with vector databases or RAG
• Experience with AI observability or evaluation tools such as Langfuse, promptfoo or similar
• Experience in IT services, MSP, SaaS or client-facing technology environments
• Familiarity with AI governance, compliance or vendor-risk concepts

What Success Looks Like

During the first 3–6 months, you will be expected to:

• Take defined business requirements and turn them into working AI automations
• Build integrations between LLMs, APIs and business systems
• Develop and troubleshoot agent workflows
• Test AI outputs and improve reliability and accuracy
• Document the solutions you build
• Follow established security and development practices
• Progressively take ownership of more complex AI workflows
• Work effectively with senior engineers and incorporate technical feedback

You will not be expected to independently architect an entire enterprise AI platform from day one. The role is designed for someone who already has practical AI/automation experience and wants to develop deeper production engineering capability with the support of an experienced technical team.