Salary range: up to £50,000

Location: Birmingham

Company Overview

At Drivvn, we're on a mission to transform how people buy and lease vehicles and we'd love for you to be part of it. As proud winners of the Culture100 Award, we're recognised not just for our innovation, but for putting our people at the heart of everything we do. Since launching in 2020 as part of the TCC Group, we have been working with major automotive brands like Stellantis, Ford, Volvo, and Volkswagen to deliver seamless digital retail experiences. More recently, we've expanded into vehicle leasing, collaborating with forward-thinking partners such as MHC and Leasys. Our platform supports the entire automotive sales and leasing journey, from vehicle configuration to financing, with real-time integration and omnichannel capabilities that put the customer in control. Our platform handles millions of real-time pricing calculations and inventory updates, integrating deeply with OEM systems, DMS platforms, and finance providers. We're currently focused on the European market, but we're thinking big and have exciting plans for global expansion. In FY25, we generated over £8 million in revenue and we know that our success is all thanks to the brilliant people who make up our team.

Primary Purpose & Scope

As a Site Reliability Engineer, you will join our platform engineering team with a clear focus on application performance and production reliability. You will live in our observability tooling, Datadog in particular, spotting slow endpoints, error spikes and resource bottlenecks across our multi-tenant automotive SaaS platform, diagnosing them down to the code, and working with the owning teams to get fixes prioritised and delivered. You’ll also have the opportunity to contribute, alongside our Senior Platform Engineers, to how we use AI-driven automation, Model Context Protocol (MCP) integrations and agentic workflows across the platform.

Performance & Observability

Own day-to-day use of Datadog across our platform, using APM, distributed tracing, logs and infrastructure metrics to find and prioritise performance issues across storefronts
Diagnose performance problems to root cause in our PHP/Symfony and Node.js services, including slow database queries, N+1 patterns, cache misses, PHP-FPM saturation and memory pressure
Build and maintain Datadog dashboards, monitors and SLOs as code using Terraform, so every service has meaningful, version-controlled signals
Run a regular performance review with Engineering Managers, tracking the top issues, trends and the impact of fixes over time

Reliability & Incident Response

Turn findings into clear, evidence-backed tickets for the owning team, with traces, metrics and a proposed fix, and follow them through to delivery
Maintain the performance and reliability backlog in Linear, tracking remediation progress with Engineering Managers and escalating unresolved reliability risks
Raise pull requests directly for well-scoped fixes where it is quicker than handing off
Respond to alerts and incidents, using runbooks to restore service efficiently, and contribute to post-incident reviews with clear follow-up actions
Once you’re up to speed on the platform, join our on-call rota to support production incidents

Infrastructure & Automation

Work with fellow platform engineers on our Azure and AKS infrastructure, managed with Terraform and deployed via GitOps (ArgoCD)
Tune alerting to reduce noise and make sure the right team is paged for the right problem
Write automation (Python, Bash, or similar) to reduce manual investigation and repetitive operational work
Apply a security-conscious mindset to everything you build, including secrets management and least-privilege access for observability tooling

About you

Essential Skills & Experience

Hands-on experience using an APM / observability platform to investigate production performance issues; Datadog strongly preferred, but New Relic or Dynatrace experience transfers well
Working knowledge of PHP (ideally Symfony and Doctrine), with the ability to read unfamiliar code, profile it and propose fixes
Good understanding of web application performance: database query optimisation, caching strategies, HTTP and CDN behaviour, and runtime tuning
Practical experience with Terraform, ideally including managing monitors or dashboards as code
Practical knowledge of running services on Kubernetes and a major cloud provider (Azure preferred)
Solid scripting skills (Bash, Python or similar) and confident with Git and Linux
Able to communicate findings clearly and persuasively, turning data into actions that other teams understand and commit to

Desirable Skills & Experience

Datadog certifications or deep experience with Datadog features such as SLOs, Watchdog, Continuous Profiler or Database Monitoring
Experience with Node.js/NestJS services and frontend performance (Core Web Vitals)
Experience defining SLOs, SLIs and error budgets
Experience with AI/ML tooling and patterns, including LLMs, AI-assisted development, or building MCP integrations that connect AI agents to observability tools
Experience supporting microservices architectures in a multi-tenant SaaS environment
Familiarity with ArgoCD, GitLab CI, Helm or Kustomize

Personal Attributes

Curious and persistent: enjoys digging into a slow trace until the real cause is found
Data-driven, letting evidence rather than opinion decide priorities
Comfortable challenging and following up with other teams, constructively and without needing to be asked
Keen to learn and grow towards owning reliability standards across the engineering organisation
Calm and methodical under pressure during incidents

We’ll let you know if you’re invited to an interview or not. But, as a small team with a lot of applications to consider, we can’t give individual feedback on each application.

Site Reliability Engineer