{"id":2774445,"url":"https://alion.io/job/simply-biz-ltd-cloud-platform-engineer","title":"Cloud Platform Engineer","company":{"id":2551319,"name":"Simply Biz Ltd","domain":"wearefintel.com","url":"https://alion.io/company/wearefintel","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Pinpoint","truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":72000,"max_usd":156000,"period":"year","method":"role_country_seniority_unknown","sample_n":204},"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Ansible","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"BigQuery","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"GitOps","optional":false},{"name":"Go","optional":false},{"name":"Google BigQuery","optional":false},{"name":"IAM","optional":false},{"name":"Incident Management","optional":false},{"name":"Kubernetes","optional":false},{"name":"Least Privilege","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"OpenTofu","optional":false},{"name":"Pulumi","optional":false},{"name":"Python","optional":false},{"name":"Terraform","optional":false},{"name":"Zero Trust","optional":false}],"status":"live","first_seen_at":"2026-10-16T07:48:44Z","employer_posted_date":"2026-10-16","last_verified_at":"2026-10-20T13:15:20Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Design the Platform Behind Every Product, Data Insight and AI Innovation\nAs a sole contributor, you'll Lead the design and operation of a modern multi-cloud platform that underpins engineering, data and product teams across the business.\nYou will:\nCreate self-service platforms, golden paths and developer tools that enable teams to ship quickly without managing cloud complexity.\nBuild AI-ready infrastructure, guardrails and automation that support both human engineers and autonomous AI agents.\nChampion a zero-trust, secure-by-default approach across identities, networks, workloads and data\nPartner with data teams to optimise cloud data platforms, pipelines and analytics environments that power business-critical insights.\nWhat you'll do\nDesign, 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.\nBuild 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.\nDeliver everything as code: infrastructure-as-code, GitOps, reusable modules, CI/CD pipelines and policy-as-code guardrails.\nLeverage AI agents extensively to automate and optimise platform work - provisioning, cost and performance optimisation, incident response, remediation and documentation.\nPrepare 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.\nEmbed 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.\nApply SRE practices - SLOs/SLIs, observability, capacity planning, resilience and blameless incident management - to keep the platform reliable and cost-efficient.\nPartner 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.\nMentor engineers, set technical direction and champion strong platform and security engineering standards across the organisation.\nWhat you'll need to succeed:\n Essential requirements:\nExtensive hands-on experience designing, building and operating production cloud infrastructure at senior or lead level.\nMulti-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).\nStrong background in modern hybrid-cloud architecture and connecting cloud with on-prem/edge environments.\nDeep infrastructure-as-code and automation skills (e.g. Terraform/OpenTofu, Pulumi, Ansible), GitOps and CI/CD, plus containers and orchestration (Docker, Kubernetes).\nProven experience building internal developer platforms, self-service golden paths and platform-as-a-product to abstract away cloud complexity for engineering teams.\nPractical experience using AI agents / LLM-based tooling to automate and optimise infrastructure work, and interest in designing infrastructure that AI agents can operate safely.\nStrong 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.\nSolid programming/scripting ability (e.g. Python, Go) and strong observability, reliability and cost-optimisation practices.\n Desirable requirements:\nExperience working as a Site Reliability Engineer (SRE) with SLOs/SLIs, error budgets and incident management.\nA third top-tier cloud certification, or specialist security/Kubernetes certifications (e.g. CKA/CKS).\nSignificant 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).\nExperience preparing environments for autonomous/agentic workloads - sandboxes, scoped machine identities, approval workflows and audit trails.\nExperience in a regulated or fintech environment.\n Your approach to work:\nPragmatic and hands-on, with a strong bias for automation and eliminating toil.\nProduct mindset - you treat internal engineers (human and AI) as your customers and obsess over their experience.\nSecurity- and reliability-first, collaborative, and comfortable leading and mentoring.\nImportant to know:\n Location:\nWe 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.\nRight to Work:\nApplicants must already hold a legal right to work in the UK without time restrictions and without the need for future sponsorship. 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