{"id":3801081,"url":"https://alion.io/job/qube-research-technologies-cloud-observability-platform-engineer-contractor","title":"Cloud Observability Platform Engineer (Contractor)","company":{"id":706156,"name":"Qube Research & Technologies","domain":"qube-rt.com","url":"https://alion.io/company/qube-research-and-technologies","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":90,"open_postings":182,"ghost_share":0,"stale_share":0.192,"repost_share":0,"time_to_fill_p50_days":140,"computed_at":"2026-11-07T05:47:08Z"}},"role":"DevOps","role_family":"DevOps","seniority":null,"employment_type":"contractor","work_mode":"on_site","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":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Alertmanager","optional":false},{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon EKS","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Grafana","optional":false},{"name":"Kubernetes","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"PagerDuty","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"Terraform","optional":false},{"name":"VictoriaMetrics","optional":false}],"status":"live","first_seen_at":"2026-07-23T13:01:20Z","employer_posted_date":"2026-11-05","last_verified_at":"2026-11-08T01:54:07Z","board_verified":true,"closed_at":null,"days_open":107,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":107},"description":"Cloud Observability Platform Engineer - Contract \nQube Research & Technologies (QRT) is a technology and data-driven quantitative investment manager. We build systems that directly support research, trading and engineering activity. \nAs our cloud estate scales, observability can no longer be treated as a set of dashboards or one-off integrations. We need standard patterns for telemetry collection, storage, alerting, service ownership, onboarding and team adoption across a large, multi-account AWS estate. \nWe already operate an established observability capability supporting our on-premises platforms. This role exists to help build the equivalent capability across our cloud estate. We are looking for engineers who have successfully built similar capabilities before and can apply those lessons here. \nWe are looking for hands-on Cloud Observability Platform Engineers to help build the foundations for cloud observability across AWS and EKS/Kubernetes. \nThis is a Platform Engineering role, not a dashboard-building role. \nWhat You'll Do \nHelp design and build the standard cloud observability patterns for AWS and EKS. \nBuild telemetry collection and distribution at scale across a large, multi-account AWS estate. \nTranslate AWS telemetry into patterns that integrate cleanly with our existing metrics, logs and alerting platforms. \nDeploy observability components, including patterns that avoid circular dependencies where the observability platform relies on itself to remain observable. \nIntegrate cloud telemetry with inventory and service ownership data, so alerts and dashboards map back to real services and accountable owners. \nBuild or integrate logs, metrics and alerting platforms, including storage, routing, retention and PagerDuty integration. \nSupport retrospective deployment of observability standards across an existing cloud estate. \nBuild repeatable onboarding patterns so new cloud workloads adopt observability consistently from day one. \nBuild user configuration automation for alert rules, scrape targets, dashboards and standard team-consumable patterns. \nReduce operational toil through automation, standardisation and clear platform patterns. \nWork closely with Observability, Cloud, Platform Engineering and service-owning teams to make the platform practical to adopt. \nSuccess depends on making cloud observability easier to adopt than bespoke alternatives while continuously improving the platform as the cloud estate evolves. \nEngineers Who Thrive In This Role \nYou have previously built or significantly expanded cloud observability capabilities in production environments. \nYou automate repetitive work rather than documenting manual processes. \nYou ask questions before proposing solutions. \nYou recognise when you do not yet understand the problem. \nYou deliberately discover how systems actually work before committing to a design. \nYou adapt your approach as new information becomes available. \nYou like solving root causes rather than symptoms. \nYou are comfortable working across infrastructure, cloud, Kubernetes, telemetry, automation and people. \nYou are pragmatic about balancing engineering quality, usability and delivery. \nYou can make progress without waiting for perfect requirements. \nYou understand that platform adoption matters as much as technical design. \nYou are comfortable owning outcomes, not just completing tickets. \nTechnologies And Areas We Expect You To Work Across \nOur current environment includes technologies such as AWS, EKS/Kubernetes, OpenTelemetry, CloudWatch, Prometheus-compatible metrics, VictoriaMetrics, VictoriaLogs, Alertmanager, Grafana, PagerDuty, infrastructure as code, CI/CD, automation, service catalogues, inventory data, Terraform, Python and Go. \nExperience with VictoriaMetrics, VictoriaLogs, Alertmanager, Terraform, Python, Go or similar tooling would be useful, but strong engineers usually learn missing tools quickly. \nWe are more interested in engineers who understand the underlying concepts and have successfully applied them in production than engineers who have experience with one particular vendor product. \nWhy This Role Exists \nWe have an established observability capability supporting our on-premises platforms. As our cloud estate grows, we are building the equivalent capability across AWS. \nThis role exists to accelerate that work by bringing practical experience of designing, building and scaling cloud observability capabilities in production environments. We are looking for engineers who can help us avoid common pitfalls, challenge our assumptions where appropriate, and build a platform that engineering teams naturally adopt. \nWhat Matters Most \nWe are far more interested in: \nEngineering judgement \nCloud platform experience \nObservability fundamentals \nAutomation \nSystems thinking \nCuriosity \nPragmatism \nAbility to work across teams \nAbility to discover and understand unfamiliar systems \nAbility to adapt as new information becomes available \nEvidence of learning from previous production experience \nthan experience with one specific vendor product. \nThis is a hands-on production role. You will help build the cloud observability capability that other engineering teams will rely on. \nWhat Success Looks Like \nSuccessful engineers in this role typically leave behind: \nRepeatable onboarding patterns for new cloud workloads. \nStandard observability patterns that engineering teams adopt consistently. \nReduced manual effort required to onboard and operate cloud services. \nTelemetry that is consistently linked to service ownership and operational responsibility. \nA cloud observability capability that is easier to adopt than building bespoke alternatives. \nCommon Anti-Patterns \nTreating observability as dashboards rather than a platform capability. \nOptimising for tools rather than outcomes. \nWaiting for perfect requirements before making progress. \nBuilding systems that are technically correct but difficult for teams to adopt. \nAssuming teams will use a platform simply because it exists. \nCreating manual onboarding processes that do not scale. \nIgnoring ownership, inventory and service context when building alerts or dashboards. \nDefending an initial design instead of adapting when new information becomes available. \nBuilding observability systems that create circular dependencies or cannot be debugged when they fail. \nThe challenge is not deploying monitoring tools. \nThe challenge is building a cloud observability capability that scales across AWS, integrates with service ownership, supports both existing and new workloads, and survives contact with real engineering teams.","description_format":"text","description_chars":6631,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Hedge Funds & Alternative 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