Automation Engineer

Locations:
Liverpool, GB – L3 1NW

• Glasgow, GB – G2 1EH

• London, GB – EC2V 7QN

At Rathbones, we help people invest their money well, so they can live well. That means more than financial returns – it’s about helping people feel confident in their decisions and supported in their future. We don’t just manage money, we guide people through life’s big moments, helping them stay on track and focus on what matters most.

We’re proud to be one of the UK’s leading wealth managers, with over £109bn
* in assets under management and 20+ offices across the UK and Channel Islands. We’re a FTSE 250 company with national reach and a local feel – and we’re growing.
* As of June 2025

Role

Title:

Automation Engineer

Division: Technology

Location: Glasgow, Liverpool, London

Reports to: Automation Product Owner

Working pattern: Hybrid

Design, build and run AI‑powered automations that improve speed, quality and colleague experience. The Automation Engineer will engineer copilots, agents and AI‑first workflows on Microsoft platforms, grounded in enterprise data and delivered with strong controls. You’ll still use classic automation where it fits, but your default mindset is AI then automate—leveraging Copilot Studio, Azure OpenAI, and Power Platform to solve real business problems end‑to‑end.

• AI & Agent engineering – Build secure, reliable copilots/agents in Copilot Studio (topics, actions, plugins, triggers), orchestrating tasks, decisions and integrations across M365 and line‑of‑business systems.
• Generative workflows – Design RAG‑grounded (retrieval‑augmented) workflows using Azure OpenAI with Graph/data connectors; optimise prompts, grounding, safety and evaluation.
• Power Platform delivery – Implement Power Automate (cloud/desktop) flows and Power Apps where appropriate; create reusable connectors/components; apply DLP policies.
• Systems integration – Integrate with APIs (REST/JSON), SharePoint/Teams/Outlook, CRM, data platforms and event triggers; handle identity, permissions and audit.
• Quality, reliability & support – Write testable solutions, instrument for telemetry, monitor for drift, and iterate based on usage data and user feedback.
• Process design – Partner with SMEs to map AS‑IS/TO‑BE, prioritise opportunities, and choose the right tool (agent, gen‑AI, workflow, RPA) for the job.
• Continuous improvement – Track emerging features, evolve patterns/playbooks, and mentor colleagues through show‑and‑tell sessions and code reviews.

• Strong problem‑solving, pragmatic delivery, and comfort with rapid iteration.
• Clear communicator who can explain trade‑offs and make defensible technical choices.
• Disciplined engineering habits: testing, observability, documentation, and secure coding.
• Proven ability to turn ambiguous business needs into working AI agents and automations.
• Copilot Studio – topics, actions, plugins, Power Automate triggers, knowledge sources; lifecycle, environments and ALM.
• Microsoft 365 & Graph – SharePoint, Teams, Outlook;
  Graph APIs/connectors; permissions & governance.
• Azure AI Foundry (AI Studio) – Prompt Flow orchestration, evaluation flows, model catalog deployments, vector search/RAG pipelines, safety configuration, monitoring and AI project lifecycle management.
• Dev fundamentals – Git/Azure Dev Ops, CI/CD, environment strategy, secure secrets management.
• RPA experience (e.g., Blue Prism) for legacy/desktop use cases;
  UiPath/Automation Anywhere exposure a plus.
• Scripting – Power Shell and/or Python for utilities, data prep and connectors.
• Power BI for light analytics/telemetry visualisation.
• Test automation (unit, integration, contract tests) and chaos/latency testing for agents.
• Basic front‑end skills for internal tools (e.g., Fluent UI, react – nice to have).

• AI agents and automations are delivered to production safely, with clear measurable benefits (time saved, quality uplift, improved colleague experience).
• Solutions are secure, compliant and supportable: documented build/runbooks, monitored performance, controlled access, and auditable changes.
• Automation and AI patterns are reusable and scalable (components, connectors, standards), reducing…