AI Engineer

THE ROLE

DOXA's AI Automation Engineers transform documented business workflows into production-ready AI applications, agents, automations, and integrations. You won't spend your time inventing AI models; you'll build practical systems that eliminate manual work and help clients scale.

REQUIREMENTS

Education: Graduate of Information Technology, Computer Science, or any related course

Experience:

• 3+ years of experience building automation, integrations, or business applications.
• Experience writing and debugging your own code. Proficiency in Python is preferred; experience with other languages commonly used in AI and machine learning engineering—such as C++, C#, or JavaScript/TypeScript—will also be considered. Experience with SQL is strongly preferred.
• Experience with LLM platforms (OpenAI, Claude, Gemini or similar).
• Experience with automation tools such as Make, n8n, Zapier, or Microsoft Power Platform.
• Experience using common business platforms, CRM systems, and backend tools such as: Airtable, Notion, HubSpot, Salesforce, or Supabase, to build solutions and improve workflows.

Skills:

• Strong systems thinking, documentation, and communication skills.
• Curiosity and willingness to continuously learn emerging AI tools.

Characteristics:

• The perfect candidate enjoys taking a defined problem and creating systems to solve it.
• Think in systems and workflows,
• Love integrating tools, enjoy building and iterating, and can communicate effectively with business users.

ESSENTIAL FUNCTIONS

• Leverage common industry AI models to train custom agents
• Integrate business systems using APIs, automations, internal applications, and workflow solutions.
• Translate approved workflow blueprints into technical solutions.
• Write tests for code in addition to user testing and QA with the goal of continuously improving deployed solutions for speed, quality, and scalability.
• Document playbooks, SOPs, and technical handoff guides.
• Continuously improve deployed solutions for speed, quality, and scalability.
• Collaborate with client stakeholders to clarify implementation requirements.

WHAT SUCCESS LOOKS LIKE (First 90 days)

• Training and certification program conducted by the AI Officer Institute
• Deliver production-ready automations
• Reduce manual work for client teams
• Create reusable documentation and playbooks