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, you'll identify automation opportunities, deliver reliable solutions, and continuously improve internal tools and workflows that power Paymentology's 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 , it’s not just about building great payment technology, it’s about building a company where people feel they belong and their work matters. You’ll be part of a diverse, global team that’s genuinely committed to making a positive impact through what we do. Whether you’re working across time zones or getting involved in initiatives that support local communities, you’ll 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 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
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

Software Engineer - Automation