Senior Automation Specialist

The role

We're hiring a Senior Automation Specialist to automate the operational work that runs tem, the work that sits outside Product and Engineering.

You'll partner directly with our Engine Leads to find manual processes and replace them with automation that holds up. This is hands-on and AI-first. You'll build agents, reasoning layers, and integrations using coding agents like Claude and Codex alongside n8n, and you'll ship them inside tem's own stack (GitHub, AWS, S3, TypeScript), so they last, rather than becoming next quarter's clean-up job.

You'll report to the Engine Ops Lead.

In this role you will:

• Design and maintain the reasoning layer for our operational engines: workflows that route and action tasks on business logic, not just move data between systems.
• Translate manual processes into automation with our Engine Leads, iterating fast on real operational feedback.
• Build agents with Claude, Codex, or equivalent, backed by evals and manual QA, shipped through tem's own GitHub and AWS stack rather than new vendor tools.
• Own delivery end to end, from discovery through to production, monitoring, and iteration, measuring yourself on hours reclaimed.

What you'll do

Build the reasoning layer

• Design and maintain the automation and reasoning layer for our operational engines: workflows that route and action tasks on business logic, not just move data between systems.
• Codify business rules, build data-quality gates, and define the safety valves that know when to hand a task to a human instead of an agent.
• Build agents with Claude, Codex, or equivalent that take on real operational volume. Each one is prompted, tested against real data, measured on precision and recall, iterated, and shipped only once it clears an agreed bar.

Partner with Engine Leads

• Work directly with the domain experts across Payments & Debt, Tendering & Partner Activation, and other operational areas to learn the business logic and turn manual processes into automation.
• Move where the impact is. You'll shift priorities to whichever engine stands to gain the most from automation.
• Iterate on real operational feedback, not on what looked right in testing.

Integrate and ship properly

• Connect internal platforms and third-party services using APIs, webhooks, and workflow tools (n8n and equivalent). You're comfortable in the messy middle, joining up systems that were never built to talk to each other.
• Build and maintain frontend apps in TypeScript, using tem's AWS-native stack (databases, S3) for storage, deployed through GitHub and GitHub Actions.
• Ship a great automation today over a perfect one next month, but never skip the eval and manual QA that prove it works before it touches live data.

Own delivery end to end

• Take problems from discovery through to production, monitoring, and iteration. You'll act as the product manager for internal efficiency.
• Measure success in manual hours removed each week, and report it as a real metric.
• Own the errors in your workflows and respond to them, improving each automation on the back of real-world use.

Enable the team

• Keep pace with what's new in AI (models, agent frameworks, prompting techniques) and bring it back into what you build.

What we're looking for

Must-haves

• 3–5 years in automation roles, with a real portfolio of hours reclaimed: specific, provable examples of code replacing manual work, not just prototypes.
• Comfort in the messy middle of API integration, connecting systems that were never designed to talk to each other.
• Deep experience with low-code automation platforms (n8n or equivalent), and hands-on experience building agents with Claude, Codex, or similar tooling as part of a real logic flow, not just prompting a chatbot.
• A systems thinker who can map a messy human process into clean architecture, and ship it inside an engineering stack.
• A real testing habit (evals plus manual QA), paired with a bias for shipping a great automation today over a perfect one next month.
• Comfort partnering directly with non-technical domain experts and turning their process knowledge into working automation.

Bonus points

• Experience in high-growth startups or operations-heavy environments (fintech, energy, logistics, e-commerce).
• A background in data engineering or business intelligence.
• Active in the AI tooling landscape, and quick to bring what you find back to the team.