Job Details

Paymentology is seeking a remote Software Engineer - Automation with 3-5 years of experience to design, develop, and maintain internal tooling solutions. The role involves integrating automation and AI capabilities into internal systems and SaaS platforms.

An Automation Engineer designs, develops, and maintains internal tooling solutions that enhance operational efficiency and streamline support processes. This role focuses on building and integrating automation solutions across internal systems and SaaS platforms, applying AI/Agent/MCP capabilities where they add clear value.

Recommended Experience: 3-5 years of experience in software development, automation engineering, internal tooling development, or AI integration Experience working cross-functionally with Product, Engineering, and Support teams to deliver automation initiatives Proven track record of optimising workflows, reducing manual processes, and improving operational efficiency Interest and personal exploration of latest AI, Agent, MCP and other related technologies Technical skills: Proficiency in Python and/or Node.js for automation and software development Familiarity in web technologies (HTML, CSS, JavaScript) and API development (RESTful, GraphQL) Experience with server-side frameworks such as Express.js (Node.js), Django/Flask (Python), or Spring Boot (Java) Proficiency in scripting languages (e.g. Bash, Python) for automation and integration tasks Familiarity with AI frameworks (A2A, ADK, LangGraph, LangChain) and AI platforms, APIs, and tooling

What you get to do: Build and maintain automation solutions: Develop, maintain, and improve internal tooling solutions that streamline operational processes Integrate SaaS platforms (e.g. HubSpot, Zendesk) with internal systems using APIs and web technologies Leverage workflow automation platforms (e.g. n8n) to rapidly design, prototype, and deploy automation flows Apply AI and intelligent automation: Evaluate where AI-driven solutions can meaningfully improve workflows, tooling, and internal processes Integrate AI services and platforms (e.g. LLMs, classification, summarisation, routing, decision support) into existing tools and automation pipelines Design automation workflows that incorporate AI responsibly, with appropriate safeguards, observability, and human-in-the-loop controls Collaborate and deliver: Partner with Operations teams to identify inefficiencies and opportunities for automation Collaborate with Product, Engineering, and Support teams to design and deliver automation and AI-enabled tooling Act as a technical advisor on automation approaches, trade-offs, and best practices