Team Lead - Platform Engineering (London)

Fresha is entering its next phase of global scale, and the Platform team plays a vital role in making that growth fast, safe, and sustainable.

As a Platform Engineering Team Lead, you will be accountable for the team’s performance and outcomes — ensuring delivery is predictable, communication is proactive, systems are well-architected, and operational standards are upheld.

With the rapid acceleration of AI and automation, this is a unique moment to transform how platforms are built and operated — reducing toil, improving reliability, and enabling smarter, faster engineering decisions.

You will support Fresha’s growth by driving infrastructure readiness, aligning platform strategy with business outcomes, and applying AI where it delivers real operational leverage.

We care deeply about customer impact, even when the work is internal - platform improvements ultimately exist to help Fresha deliver better experiences to customers.

Docker

AWS EKS

Kafka / AutoMQ for asynchronous messaging

Elixir & Ruby for core services

gRPC for inter service communication

GraphQL for API ingress

Next.js / TypeScript for frontend

PostgreSQL (RDS) for persistent storage

GitHub Actions (primary CI), with Jenkins & Argo Workflows for legacy pipelines

Redis for key/value storage

Terraform for infrastructure as code

Python and GoLang for our Platform tools

Datadog, Sentry for observability and incident response

Apply AI-assisted approaches to reduce toil, improve reliability, and support platform decision-making where it creates clear value

Align technology direction with broader company strategy and operational priorities

Define and evolve infrastructure architecture to support multi-region deployments

Implement with AI-assisted detection, triage, and automation to improve signal quality and reduce manual effort

Extend monitoring, alerting, and observability capabilities across services

Make operational data easy to access, understand, and act on

Drive cross-functional initiatives across Product, Engineering, and Security stakeholders

Own the reliability and performance of the platform, ensuring the team consistently delivers high-quality results

Scope, prioritise, and deliver platform initiatives with clear outcomes and accountability

Set goals that are ambitious but achievable, without compromising technical standards

Ensure the team is clear on expectations and empowered to make value-added decisions

Develop engineers through coaching, delegation, and feedback

Foster continuous learning through retros, documentation, and knowledge-sharing

Own onboarding and team health, ensuring engineers are set up for success

Have proven experience as an engineering leader, driving high-impact outcomes across platform, infrastructure, or reliability teams

Bring hands-on experience applying automation and AI/LLM-based tools to improve observability, incident response, and reduce operational toil

Strong technical background across infrastructure, cloud platforms, and distributed systems

Knowledge of cloud architecture, workload management, DevOps, and SRE principles

Experience with AWS (EKS, RDS, S3, CloudFront), or equivalent platforms on GCP or Azure

Understanding of Linux and networking fundamentals (TCP/IP, DNS, firewalls, load balancing, VPNs)

Demonstrate strong programming and automation skills in Python, Go, or Bash, and use Infrastructure as Code (Terraform) to build repeatable, low-risk systems

Practical experience building observability systems across metrics, logs, and traces, using tools such as Datadog, Grafana, ELK, Sentry, and OpsGenie

Creative problem-solving mindset, with the ability to simplify complex systems and unlock scalable solutions

Comfortable operating in a fast-paced, rapidly evolving environment with high ownership, ambiguity, and strong accountability

Have experience with Claude code

Screen Stage - Video-call with a member from the Talent Team (45-60min)

1st Stage - Technical video/In-person interview with the team (90min)

2nd Stage - Technical Video/In-person interview with Team (up to 1.5 hours)

Final Stage - Video interview with VP of Engineering & CTO (60min)

We aim to finalise the entire interview process and deliver feedback within 4 weeks.

Every job application received is reviewed manually by our talent team. While we strive to assess applications within 7 days, the sheer volume of talented individuals expressing interest may occasionally extend this timeframe

At Fresha, we are creating a culture where individuals of all backgrounds feel comfortable.

We want all Fresha people to feel included and truly empowered to contribute fully to our vision and goals. Everyone who applies will receive fair consideration for employment.

We do not discriminate based on race, colour, religion, sex, sexual orientation, age, marital status, gender identity, national origin, disability, or any other applicable legally protected characteristics in the location in which the candidate is applying.

If you have any accessibility requirements that would make you more comfortable during the interview process and/or once you join, please let us know so that we can support you.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.