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Senior Site Reliability Engineer | Senior Platform Engineer | Applied AI Engineer | London & Remote

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Executive Hurdles Recruitment is currently supporting two businesses with three senior technology appointments — two in London and one fully remote across the UK.

 

Role 1 — Senior Site Reliability Engineer (Senior SRE)

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Leading UK Payment Technology Business | London Hybrid

  • Salary: Up to £90,000 + 10% cash benefit + 10% non-contributory pension + discretionary bonus (5% realistic)

  • Type: Permanent | Hybrid | 1 day per week in London office

  • Sponsorship: Not available​

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This is the only Senior SRE in the team — a high-visibility appointment that will represent SRE practice across the wider business and help shape the function as it grows. The team operates on a build it, own it, run it philosophy within a large, process-driven financial services environment.

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What the role involves:

  • Drive and embed operational characteristics across products and services — availability, performance, monitoring, incident response, capacity planning and change management

  • Define error budgets and balance risk against reliability

  • Build, improve and automate release processes and pipelines

  • Coach and guide colleagues across the wider team — leading where required

  • Engage with a broad stakeholder group including Delivery and Engineering Managers

 

What we are looking for:

  • Hands-on Kubernetes — essential

  • Hands-on Azure — essential

  • Terraform — essential | Bicep — desirable

  • CI/CD pipeline design, release automation and observability

  • Grafana Stack, Log Analytics, AppInsights or equivalent

  • DevOps processes and ITSM / ServiceNow knowledge

  • Large, process-heavy business background — financial services not required

  • Strong stakeholder management — essential

 

Role 2 — Senior Platform Engineer

 

Leading UK Payment Technology Business | London Hybrid

  • Salary: Up to £90,000 + 10% cash benefit + 10% non-contributory pension + discretionary bonus (5% realistic)

  • Type: Permanent | Hybrid | 1 day per week in London office

  • Sponsorship: Not available

 

A high-profile platform engineering role with real ownership — designing, building and continuously improving secure, scalable and high-performing Azure platforms within a fast-moving payments environment.

 

What the role involves:

  • Design, build and deploy secure, scalable Azure platform services

  • Own and improve platform engineering tools, processes and ways of working

  • Contribute to a clean, reusable and maintainable codebase

  • Conduct proactive code and design peer reviews

  • Prioritise platform and operational issues, defects and maintenance for high availability

  • Pioneer new ideas to improve delivery lifecycles from design through to operational support

 

What we are looking for:

  • Azure hands-on: PaaS, AKS, Landing Zones, CAF, Hub & Spoke, cloud security — essential

  • Terraform and IaC: Bicep, PowerShell, JSON, Azure DevOps or Jenkins — essential

  • Kubernetes, containerisation, microservices, API Management — essential

  • Observability: Azure Monitor, Log Analytics, AppInsights, Grafana

  • Microsoft technologies: Azure Entra, Microsoft 365, Endpoint Manager

  • Configuration management: Chef, Puppet or Ansible

  • MongoDB — preferred | Disaster recovery — desirable

  • PCI DSS and financial services governance awareness — desirable

  • Any sector background considered

 

Role 3 — Applied AI Engineer

 

Remote-First AI Product Company | Fully Remote, UK-Wide

  • Salary: £85,000 – £100,000 plus equity

  • Type: Permanent | Fully Remote | UK-based

  • Sponsorship: Not available

 

A fully remote opportunity to own the space between model capability and real-world product behaviour. Our client is building AI-native applications designed to handle conversations, tasks, organisation and workflows at scale. The challenge is reliability — long-running workflows, persistent context and real-world task completion outside controlled experiments. This role exists to turn model capability into dependable product behaviour.

 

What the role involves:

  • Build and ship AI features end-to-end, from model behaviour through to the user experience

  • Design and iterate on prompts, tools, memory and agent workflows

  • Turn raw model outputs into structured, reliable and predictable behaviours

  • Debug issues across models, orchestration, infrastructure and product

  • Improve latency, cost and production reliability

  • Build lightweight evaluation frameworks around real-world performance

  • Use production signals to drive measurable improvements to models and systems

 

What we are looking for:

Essential:

  • Hands-on experience training, fine-tuning or deploying ML models

  • Strong machine learning foundations and modern neural network architectures

  • Experience taking ML or AI systems into production — beyond experimentation

  • Production-quality Python engineering

  • Experience working with LLMs, model APIs or open models

  • Experience working across model, infrastructure and product layers

  • Experience diagnosing and resolving production ML issues

 

Useful (not all required):

  • PyTorch or JAX

  • LLaMA, Qwen or similar open models

  • vLLM or other inference and serving tooling

  • Vector databases

 

This role is best suited to someone who has already been responsible for getting AI into users' hands and then making it perform reliably once it is there. If your experience has remained within research or experimentation without production ownership, this is unlikely to be the right move.

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Apply now or get in touch for a confidential discussion:

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