AI Systems & Automation Engineer

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AI Systems and Automation Engineer

Location: Remote / Philippines-based (AU/MidShift/PST)
Employment Type: Full-time

Build the AI Infrastructure That Runs an Entire Business. Design AI Systems. Automate Operations. Own Production.

At Doneverse, we're not experimenting with AI.

We're building a business powered by it.

We're looking for an exceptional AI Systems & Automation Engineer to architect, build, and operate the AI-powered systems that run our company—from intelligent workflow orchestration and decision engines to internal CRMs, operational data platforms, and production-grade AI applications.

This isn't a prompt engineering role.

This isn't a "connect a few tools together" automation role.

You'll own mission-critical systems that directly impact how our business operates every single day.

If you're passionate about solving complex engineering problems, designing scalable AI systems, and building software that eliminates manual work, we'd love to meet you.

About the Role:
This is a senior technical role with broad accountability: from workflow orchestration and decision engines to operational data platforms, internal tools, and production-grade LLM features. You will be the most senior technical authority on AI and automation topics, driving reliability, scalability, and compliance across mission-critical systems.

Key Responsibilities:

AI Systems Architecture: Design and document principled architectures, balancing deterministic logic, ML, and LLMs.
Workflow Orchestration & Automation: Build scalable, reliable workflows across no-code and custom services.
Decision Engines: Implement explainable, traceable allocation and matching systems with human-in-the-loop escalation.
Operational Data Platform: Own schemas, pipelines, and integrations across SaaS systems.
Internal Tools & CRMs: Develop CRMs, dashboards, and operational tools using low-code and framework code.
Audit & Governance: Implement approval systems, audit trails, and compliance-ready event logs.
Reporting & Observability: Deliver automated reporting, structured logs, metrics, and monitoring.
AI/LLM Engineering: Ship production-ready LLM features with evaluation harnesses and cost/latency optimization.
Reliability & Security: Own production reliability, incident response, and enforce strict access controls.
Project Delivery: Lead projects end-to-end — discovery, design, build, rollout, training, and optimization.

Qualifications:

5+ years in software or automation engineering, with 2+ years building production AI/LLM-backed systems.
Strong coding skills in Python and/or TypeScript/Node.js (both preferred).
Advanced SQL skills for complex queries and performance optimization.
Experience with workflow tools (Make.com, n8n, Zapier) and backend fundamentals (REST APIs, queues, retries).
Data warehousing expertise (BigQuery or equivalent).
Integration experience with SaaS platforms (e.g., Asana, Zoho, Slack, Google Workspace).
Track record of owning production systems end-to-end (e.g., allocation engines, workflow platforms, CRMs, data warehouses).
Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
English proficiency (CEFR C1 or above).

Preferred Skills:

Experience with agentic AI patterns, dbt, infrastructure-as-code, or event-sourced systems.
Strong systems thinking, technical documentation, and cross-functional communication.
Calm, methodical debugging under production pressure.

What We’re Looking For

Ownership mindset and engineering judgment.
Pragmatic problem-solving — choosing the simplest maintainable solution.
Curiosity about operational workflows and how systems are actually used.
Comfort being the senior technical authority on AI/automation.