AI SOLUTIONS ENGINEER

Duties & Responsibilities

Solution Architecture & Engineering

• Translate prioritised automation opportunities into robust technical designs — mapping exception paths, defining data flows, and designing for reliability before building.
• Design, build, and deploy automation using AI engineering tools (Claude Code and other agentic coding assistants, MCP, LLMs) with Python and supporting frameworks (e.g. Playwright).
• Develop custom automation agents, scripts, and integrations that automate data extraction, transformation, reconciliation, document generation, and system-to-system handoffs.
• Build and maintain MCP servers / connectors that expose internal data and tools to AI workflows in line with IT security standards.

Systems Integration & Reliability

• Architect end-to-end workflows that bridge disparate systems (ERP/finance, internal databases, spreadsheets, messaging and reporting platforms) while ensuring data integrity.
• Build integrations that connect siloed systems, progressively reducing duplicated and manually reconciled data across departments.
• Implement validation, logging, error-handling, and monitoring so automations run reliably with minimal manual intervention.

Governance & Documentation

• Build within IT’s governance framework — using managed credentials, access controls, and peer code review to established IT security standards — so automations are safe to run against production finance and operational systems, in line with data-protection requirements (PDPA).
• Author technical documentation — logic maps, API configurations, and runbooks — for long-term maintainability and easy troubleshooting.

Delivery, Enablement & Collaboration

• Partner with the process analyst and process owners — who own frontline discovery and engagement — to convert validated opportunities into deployed solutions.
• Create intuitive SOPs and training materials, and coach non-technical staff to support sustained adoption of deployed automations.
• Deliver quick wins that visibly relieve user workload.

Value Measurement

• Instrument every automation with before/after effort baselines to build a defensible record of time saved.
• Report on time savings, efficiency, error reduction, and reliability of deployed automations.

Job Requirements

• Education: Diploma/Degree in Computer Science, Engineering, or a related field (or equivalent practical experience).

Technical Skills: Python; web automation (Playwright/Selenium); data processing and scripting; version control (Git) and automated testing of deployed automations; APIs and systems integration (ERP/finance platforms, databases). AI-first automation — agentic coding tools (e.g. Claude Code, Cowork), MCP, applied LLM workflows and prompt design. Familiarity with traditional RPA (UiPath, Power Automate, VBA, pywinauto) is an advantage for legacy / no-API systems. Domain Knowledge: Strong understanding of back-end business processes — finance, accounting, reporting, or operations — enabling the engineer to bridge technical and business needs. Soft Skills: Clear technical documentation and SOP writing; ability to coach non-technical users; strong problem-solving; able to work independently and across functions. Experience: Demonstrated experience designing and deploying business process automation (RPA and/or scripted) in a corporate environment.