Cloud Platform Engineer – Senior/Lead

Fintel

Cloud Platform Engineer designing and running multi-cloud infrastructure with a focus on AI agents. Building internal platforms and embedding zero-trust security.

Posted 7/22/2026full-timeFarringdon, London • 🇬🇧 United KingdomSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in designing and operating multi-cloud and hybrid-cloud platforms, with a strong focus on infrastructure-as-code, automation, and security engineering. Proficient in leveraging AI agents for infrastructure optimization and implementing zero-trust security models.

Highest-signal resume keywords

Multi-Cloud ExperienceInfrastructure-As-CodeZero-Trust SecurityAI Agent AutomationSite Reliability Engineering (SRE)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Cloud Infrastructure DesignInfrastructure-As-CodeAutomation SkillsData Pipeline OptimizationProgramming/Scripting (Python, Go)CI/CD PipelinesContainers (Docker, Kubernetes)Observability PracticesCost OptimizationHybrid-Cloud Architecture

Soft Skills

MentoringTechnical DirectionCollaboration

Tools & Technologies

AWSMicrosoft AzureGoogle CloudTerraform/OpenTofuPulumiAnsibleBigQueryGitOps

Certifications & Qualifications

AWS Solutions ArchitectAzure Solutions ArchitectGoogle Cloud Professional Cloud ArchitectCKA/CKS

Industry Keywords

FintechRegulated EnvironmentSLOs/SLIsIncident ManagementSecrets Management

Tech Stack

Tools & technologies

AnsibleAWSAzureBigQueryCloudDockerGoKubernetesPythonTerraform

About the role

Key responsibilities & impact

Design, build and operate our multi-cloud and hybrid-cloud platform across at least two of the top-three providers (AWS, Azure and/or Google Cloud), plus on-prem/hybrid connectivity where needed.
Build and own an internal developer platform and self-service "golden paths" that make cloud infrastructure feel invisible and commoditised for engineering, data and product teams; and their AI agents.
Deliver everything as code: infrastructure-as-code, GitOps, reusable modules, CI/CD pipelines and policy-as-code guardrails.
Leverage AI agents extensively to automate and optimise platform work - provisioning, cost and performance optimisation, incident response, remediation and documentation.
Prepare the infrastructure for AI agents as first-class "engineers": safe machine identities, scoped permissions, sandboxes, approval workflows and audit trails so agents can provision and operate infrastructure within tight guardrails.
Embed a zero-trust security model across identity, network, workloads and data for both human and machine/agent identities; secure by default, least privilege, secrets management and continuous compliance.
Apply SRE practices - SLOs/SLIs, observability, capacity planning, resilience and blameless incident management - to keep the platform reliable and cost-efficient.
Partner with data engineering to design and optimise data pipelines, data stores and large-scale analytics infrastructure such as BigQuery, including query, cost and performance tuning.
Mentor engineers, set technical direction and champion strong platform and security engineering standards across the organisation.

Requirements

What you’ll need

Extensive hands-on experience designing, building and operating production cloud infrastructure at senior or lead level.
Multi-cloud experience across at least two of the top three providers (AWS, Microsoft Azure and Google Cloud), including a recognised professional-level cloud certification for each of those two providers (for example AWS Solutions Architect / DevOps Engineer Professional, Azure Solutions Architect / DevOps Engineer Expert, or Google Cloud Professional Cloud Architect / DevOps Engineer).
Strong background in modern hybrid-cloud architecture and connecting cloud with on-prem/edge environments.
Deep infrastructure-as-code and automation skills (e.g. Terraform/OpenTofu, Pulumi, Ansible), GitOps and CI/CD, plus containers and orchestration (Docker, Kubernetes).
Proven experience building internal developer platforms, self-service golden paths and platform-as-a-product to abstract away cloud complexity for engineering teams.
Practical experience using AI agents / LLM-based tooling to automate and optimise infrastructure work, and interest in designing infrastructure that AI agents can operate safely.
Strong security engineering mindset with hands-on zero-trust experience across identity, network, workloads and data — including secrets management, least-privilege IAM and machine/workload identity.
Solid programming/scripting ability (e.g. Python, Go) and strong observability, reliability and cost-optimisation practices.
Experience working as a Site Reliability Engineer (SRE) with SLOs/SLIs, error budgets and incident management is desirable.
A third top-tier cloud certification, or specialist security/Kubernetes certifications (e.g. CKA/CKS) is desirable.
Significant data engineering experience: designing and operating data pipelines and data stores, and optimising databases and large-scale data infrastructure such as BigQuery (including query, cost and performance tuning) is desirable.
Experience preparing environments for autonomous/agentic workloads — sandboxes, scoped machine identities, approval workflows and audit trails is desirable.
Experience in a regulated or fintech environment is desirable.

Benefits

Comp & perks

Location: We have multiple offices across the UK. We have a new office in London which is becoming more central to where collaborate in person. We have a flexible working policy with a few days per week in the office.
Right to Work: Applicants must already hold a legal right to work in the UK without time restrictions and without the need for future sponsorship. We are unable to provide Skilled Worker visa sponsorship.