{"id":478514,"url":"https://alion.io/job/gibson-dunn-platform-engineer-london","title":"Platform Engineer - London","company":{"id":185365,"name":"Gibson Dunn","domain":"gibsondunn.com","url":"https://alion.io/company/gibson-dunn","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":95,"open_postings":26,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":69,"computed_at":"2026-10-28T05:59:10Z"}},"role":"DevOps","role_family":"DevOps","seniority":"senior","employment_type":null,"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":{"min_usd":80000,"max_usd":162000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":61},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Ansible","optional":false},{"name":"Anthropic","optional":false},{"name":"ArgoCD","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"Bicep","optional":false},{"name":"CI/CD","optional":false},{"name":"Datadog","optional":false},{"name":"Docker","optional":false},{"name":"Function Calling","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitLab CI","optional":false},{"name":"GitOps","optional":false},{"name":"Go","optional":false},{"name":"Grafana","optional":false},{"name":"HashiCorp Vault","optional":false},{"name":"Helm","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Hybrid Search","optional":false},{"name":"ITIL","optional":false},{"name":"Jenkins","optional":false},{"name":"JFrog Artifactory","optional":false},{"name":"JUnit","optional":false},{"name":"Kubernetes","optional":false},{"name":"Kustomize","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"Playwright","optional":false},{"name":"PowerShell","optional":false},{"name":"Prometheus","optional":false},{"name":"Pytest","optional":false},{"name":"Python","optional":false},{"name":"Splunk","optional":false},{"name":"Terraform","optional":false},{"name":"Vault","optional":false}],"status":"live","first_seen_at":"2026-08-17T15:25:49Z","employer_posted_date":"2026-09-02","last_verified_at":"2026-10-28T11:19:52Z","board_verified":true,"closed_at":null,"days_open":72,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":72},"description":"Gibson Dunn is a leading global law firm, advising clients on significant transactions and disputes. Our exceptional teams craft and deploy creative legal strategies that are meticulously tailored to every matter, however complex or high-stakes. The firm’s work is distinguished by a unique combination of precision and vision.\nBased in London, the Platform Engineer will be responsible for building the reusable platforms, tools, and services that improve developer productivity, accelerate delivery, and standardize engineering practices across the firm. The role writes and ships the code behind the firm’s internal developer platform, building and maintaining self-service tooling, infrastructure-as-code modules, pipeline definitions, and automation across CI/CD, cloud, and observability, and participating in the team’s operational and on-call duties. Working under the guidance of senior engineers, this role delivers reliable, well-tested code and self-service capabilities for development teams while growing toward end-to-end ownership.\nThe platform supports conventional in-house software alongside AI workloads such as model inference, retrieval, and agent-based systems, all on a shared foundation. This role helps extend the same pipelines and reliability standards to AI workloads, while recognizing where AI demands different primitives such as evaluations, non-deterministic failure handling, token economics, and confidentiality controls.\nPrimary applications and platforms include:\nCI/CD, Source Control & Test Automation: GitHub Actions, Azure DevOps, GitLab CI, Jenkins; Git, JFrog Artifactory; Playwright, pytest/JUnit\nInfrastructure & Config as Code: Terraform, Ansible, Bicep/ARM, Helm, Kustomize; GitOps via Argo CD and Flux\nCloud & Orchestration: AWS, Azure, Docker, Kubernetes\nAI Inference & Application Infrastructure: Frontier and open-weight models via Anthropic, Azure OpenAI, and Amazon Bedrock; model gateways and routing, retrieval and hybrid search, document ingestion, tool/function calling, Model Context Protocol (MCP), and agent orchestration\nAI Evaluation & Quality: Eval harnesses and golden datasets, LLM-as-judge and human-in-the-loop review, regression suites, and red-teaming\nObservability & Monitoring: Prometheus, Grafana, Datadog, Splunk, Elastic/ELK, OpenTelemetry, including GenAI tracing and token, latency, and cost telemetry\nPlatform Security & Policy-as-Code: HashiCorp Vault, OPA/Conftest, SAST/DAST\nDeveloper Portal & Self-Service: Internal developer portal, CLIs/SDKs, and APIs\nResponsibilities include: \nDeveloper Experience & Self-Service Enablement\nBuild and maintain self-service tooling, CLIs, libraries, and templates, as version-controlled, tested code, that make it easy for teams to build, test, and ship software.\nContribute features and fixes to the internal developer platform and portal through pull requests and code review.\nProvide day-to-day support to developers using platform services, triaging and resolving requests and issues.\nSupport governed self-service access to AI platform capabilities, including model access, retrieval tooling, and evaluation workflows, so AI capabilities can move from prototype to production using standard platform patterns.\nCI/CD, Release Management & Test Automation\nImplement and maintain pipelines-as-code (e.g., GitHub Actions/Azure DevOps YAML) to established patterns, keeping builds, tests, and deployments reliable and fast.\nExecute and support release activities, following defined GitOps and change-management processes.\nWrite and maintain automated tests and quality gates within pipelines.\nImplement evaluation-based quality gates for AI systems, including evals-as-code, regression suites against golden datasets, and human-review thresholds where required.\nInfrastructure as Code & Cloud Platforms\nAuthor and maintain modular, tested infrastructure-as-code (e.g., Terraform, Helm) to provision and configure cloud and on-prem resources.\nDeploy and operate workloads across cloud platforms (AWS/Azure) and Kubernetes using GitOps (Argo CD/Flux).\nFollow tagging, cost, and configuration standards when provisioning resources.\nHelp deploy and operate AI workload infrastructure, including model gateways, retrieval services, orchestration components, and supporting cloud or Kubernetes resources.\nObservability, Monitoring & Site Reliability (SRE)\nInstrument services and implement monitoring, logging, and alerting as code using standard tooling (Prometheus, Grafana, OpenTelemetry).\nParticipate in the on-call rotation, responding to incidents and helping restore service.\nContribute to blameless post-incident reviews and implement follow-up actions in code.\nInstrument AI services for operational visibility, including tracing across prompts, tools, and agent steps, and monitoring latency, cost, token usage, and quality regressions.\nPlatform Security & Automation\nApply platform security controls and remediate vulnerabilities to defined standards, including policy-as-code checks (e.g., OPA/Conftest).\nManage secrets, access, and configuration securely using approved tooling (e.g., Vault).\nApply security and confidentiality controls for AI workloads, including prompt-injection and data-exfiltration defenses, output filtering, and access controls across prompts, retrieval, and agent tool use.\nAutomate repetitive operational tasks by writing scripts and small services.\nSoftware Engineering Standards & Collaboration\nFollow engineering standards, version-control workflows, code-review, and testing practices.\nCollaborate with platform and development teams and escalate complex issues appropriately.\nCreate and maintain runbooks, SOPs, and documentation as code alongside the tooling it describes.\nQualifications:\nProficiency writing production-quality code in Go and Python (plus PowerShell/Bash), using Git, pull requests, code review, and automated testing.\nWorking proficiency building pipelines-as-code (GitHub Actions, Azure DevOps, GitLab CI, Jenkins).\nExperience with infrastructure as code (Terraform, Ansible, Helm) and GitOps concepts.\nHands-on experience with at least one major cloud platform (AWS or Azure) and Kubernetes/Docker.\nFamiliarity with observability tooling (Grafana, Datadog, Splunk, ELK, OpenTelemetry) and basic SRE practices.\nExposure to test automation, policy-as-code, and platform security practices.\nFamiliarity with ITIL best practices (incident, change, and problem management) preferred.\nExperience with Lean or Agile methodologies preferred.\nRelevant certifications (e.g., AWS/Azure Associate, Certified Kubernetes Administrator) preferred.\nExperience:\n5+ years of experience in platform, DevOps, infrastructure, or software engineering roles.\nBachelor’s degree in Computer Science, Information Technology, Engineering, or a related field (or equivalent experience).\nExperience supporting business-critical systems, ideally within professional services, legal, or regulated environments.\nGibson Dunn will consider for employment qualified Applicants with Criminal Histories in a manner consistent with the requirements of local law.\n______\nFor technical difficulties with our online application, please contact us at . Our recruiting support team will respond as soon as possible.\n______\nGibson Dunn is committed to ensuring equal employment opportunities for all qualified applicants, including individuals with disabilities. We strive to ensure an inclusive and accessible hiring experience. The Firm will provide reasonable accommodations to qualified individuals with disabilities to enable participation in the application and recruitment process, unless doing so would impose an undue hardship, in accordance with applicable laws and regulations.\nIf you require a reasonable accommodation to complete an application, participate in an interview, or otherwise take part in the recruitment process, please contact us at . Please note, this is a dedicated email inbox established exclusively to assist applicants with accommodation request related to the recruitment process. 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Docs: https://alion.io/developers"}}