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. Working closely with cross-functional teams youll identify automation opportunities deliver reliable solutions and continuously improve internal tools and workflows that power Paymentologys operations.
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
Determine when low-code/no-code automation is appropriate versus when custom-built solutions are required
Develop and maintain clear documentation for tools integrations and automation processes
Troubleshoot and resolve technical issues related to integrations and automated workflows
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
Stay informed on emerging AI capabilities and assess their practical applicability to internal use cases
Collaborate with Product and Engineering teams to ensure AI-enabled solutions are reliable scalable and aligned with business needs
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
Ensure clear communication and alignment across teams for seamless tool integration and process optimisation
Drive continuous improvement:
Monitor and improve existing tools and automations to ensure performance reliability and usability
Identify opportunities to simplify optimise or retire tooling as needs evolve
Take a proactive problem-solving approach to improving automation efficiency and user experience
Contribute to the development and adoption of best practices for internal tooling automation and applied AI
What you can look forward to::
At Paymentology its not just about building great payment technology its about building a company where people feel they belong and their work matters. Youll be part of a diverse global team thats genuinely committed to making a positive impact through what we do. Whether youre working across time zones or getting involved in initiatives that support local communities youll find real purpose in your work and the freedom to grow in a supportive forward-thinking environment.
Travel: < 10%
Requirements:
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 for automation and software development
Familiarity in web technologies (HTML CSS JavaScript) and API development (RESTful GraphQL)
Experience with server-side frameworks such as () 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
Good understanding of integrating AI-driven capabilities into existing systems and workflows
Knowledge of SaaS platform integrations (HubSpot Zendesk etc.) and API design patterns
Understanding of CI/CD pipelines version control (Git) and DevOps practices
Key behaviors:
Problem-solving mindset: Excellent problem-solving skills with high attention to detail
Collaboration: Strong communication skills for working effectively with cross-functional teams
Independence: Ability to work independently manage multiple priorities and deliver solutions efficiently
Innovation: Proactive approach to identifying automation opportunities and applying new technologies
Quality focus: Commitment to writing clean maintainable well-tested code
Preferred:
Experience with cloud platforms (AWS Azure or GCP) and infrastructure automation
Experience with observability and monitoring tools (DataDog Grafana Prometheus)
Familiarity with containerization (Docker Kubernetes)
Knowledge of Infrastructure as Code (Terraform CloudFormation)
Experience with serverless architectures and event-driven systems
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 wher...
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. Working closely with cross-functional teams youll identify automation opportunities deliver reliable solutions and continuously improve internal tools and workflows that power Paymentologys operations.
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
Determine when low-code/no-code automation is appropriate versus when custom-built solutions are required
Develop and maintain clear documentation for tools integrations and automation processes
Troubleshoot and resolve technical issues related to integrations and automated workflows
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
Stay informed on emerging AI capabilities and assess their practical applicability to internal use cases
Collaborate with Product and Engineering teams to ensure AI-enabled solutions are reliable scalable and aligned with business needs
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
Ensure clear communication and alignment across teams for seamless tool integration and process optimisation
Drive continuous improvement:
Monitor and improve existing tools and automations to ensure performance reliability and usability
Identify opportunities to simplify optimise or retire tooling as needs evolve
Take a proactive problem-solving approach to improving automation efficiency and user experience
Contribute to the development and adoption of best practices for internal tooling automation and applied AI
What you can look forward to::
At Paymentology its not just about building great payment technology its about building a company where people feel they belong and their work matters. Youll be part of a diverse global team thats genuinely committed to making a positive impact through what we do. Whether youre working across time zones or getting involved in initiatives that support local communities youll find real purpose in your work and the freedom to grow in a supportive forward-thinking environment.
Travel: < 10%
Requirements:
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 for automation and software development
Familiarity in web technologies (HTML CSS JavaScript) and API development (RESTful GraphQL)
Experience with server-side frameworks such as () 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
Good understanding of integrating AI-driven capabilities into existing systems and workflows
Knowledge of SaaS platform integrations (HubSpot Zendesk etc.) and API design patterns
Understanding of CI/CD pipelines version control (Git) and DevOps practices
Key behaviors:
Problem-solving mindset: Excellent problem-solving skills with high attention to detail
Collaboration: Strong communication skills for working effectively with cross-functional teams
Independence: Ability to work independently manage multiple priorities and deliver solutions efficiently
Innovation: Proactive approach to identifying automation opportunities and applying new technologies
Quality focus: Commitment to writing clean maintainable well-tested code
Preferred:
Experience with cloud platforms (AWS Azure or GCP) and infrastructure automation
Experience with observability and monitoring tools (DataDog Grafana Prometheus)
Familiarity with containerization (Docker Kubernetes)
Knowledge of Infrastructure as Code (Terraform CloudFormation)
Experience with serverless architectures and event-driven systems