Platform Enablement Lead

ClearRoute

. Build golden paths for AI workloads, including templates and scaffolding for services, RAG pipelines, agents and model-backed APIs .

Posted 11/4/2026full-timeLondon • United KingdomSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and managing internal developer platforms, with a strong focus on cloud infrastructure, infrastructure-as-code, and AI workload integration. Proficient in leading teams to enhance platform capabilities and drive adoption while ensuring security and observability.

Highest-signal resume keywords

Cloud Experience With AWS, Azure Or GCPInfrastructure-As-Code Using Terraform Or PulumiKubernetes And Containers In ProductionCI/CD Design Using GitHub Actions Or GitLab CISolid Coding Skills In Python And Go Or TypeScript

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Infrastructure-As-CodeKubernetesCI/CDPythonGoTypeScriptLLM-Based ApplicationsObservability FundamentalsRAG ArchitecturesVector Databases

Soft Skills

Product MindsetCoaching TeamsGathering FeedbackOnboarding SessionsClient-Facing Delivery

Tools & Technologies

TerraformPulumiGitHub ActionsGitLab CIOpenTelemetryGrafanaDatadogArgo CDFluxLangChain

Certifications & Qualifications

ITILCKACKADCloud Certifications

Industry Keywords

AI GovernanceEU AI ActISO/IEC 42001GDPRRegulated Sectors

Tech Stack

Tools & technologies

AWSAzureCloudFluxGoogle Cloud PlatformGrafanaKubernetesPythonTerraformTypeScriptGo

About the role

Key responsibilities & impact

Build golden paths for AI workloads, including templates and scaffolding for services, RAG pipelines, agents and model-backed APIs
Run the internal developer platform, including developer portal, service catalogue, self-service environments and infrastructure-as-code modules
Standardise access to LLM providers and self-hosted models through a shared gateway with routing, rate limits, caching, cost tracking and key management
Integrate evaluation frameworks, prompt and model versioning, and regression testing into delivery pipelines
Embed PII handling, prompt-injection defences, content filtering, audit logging and policy-as-code with security teams
Provide tracing, token-usage and latency dashboards, plus cost visibility per team and feature
Write documentation and runbooks, run onboarding sessions and office hours, pair with product teams, and gather platform feedback
Track platform adoption, lead time and friction points, removing major blockers each quarter
Lead a team focused on Azure platform foundations, including identity, networking, CI/CD, observability and environment management
Coach teams to adopt platform capabilities and enable faster, safer AI feature delivery

Requirements

What you’ll need

4+ years in platform, DevOps, SRE or infrastructure engineering, with time spent supporting other engineering teams
Strong hands-on cloud experience with AWS, Azure or GCP
Experience with infrastructure-as-code using Terraform, Pulumi or similar
Kubernetes and containers in production, including deployment patterns, scaling and troubleshooting
CI/CD design and ownership using GitHub Actions, GitLab CI or similar
Experience with GitOps tooling such as Argo CD or Flux
Solid coding skills in Python and at least one of Go or TypeScript
Practical experience building or integrating with LLM-based applications, including provider APIs, embeddings, vector stores or RAG patterns
Observability fundamentals: metrics, logs and distributed tracing using OpenTelemetry, Grafana, Datadog or similar
Product mindset about internal platforms, treating developers as customers and measuring adoption
Desirable: experience with RAG architectures and vector databases such as Pinecone, Weaviate, pgvector or Azure AI Search
Desirable: familiarity with LangChain, LlamaIndex or Model Context Protocol (MCP)
Desirable: experience with LLM observability and evaluation tools such as LangSmith, Langfuse, Arize or Weights & Biases
Desirable: experience hosting or serving open-weight models such as vLLM, Hugging Face or SageMaker
Desirable: awareness of AI governance and regulation, including EU AI Act, ISO/IEC 42001 and GDPR
Desirable: ITIL, CKA/CKAD or cloud certifications
Desirable: experience in consultancy or client-facing delivery, ideally in regulated sectors such as energy or financial services

Benefits

Comp & perks

Genuine hybrid working
Home office budget
Time off when life needs it, including birthday leave
Profit share
Private healthcare
Confidential employee assistance program covering counselling, mental health support, and financial wellbeing
Interest-based communities, including running and book clubs
Women in Tech group
Monthly socials
Cross-regional events
Learning budgets
Udemy access
Clear career framework
Internal mobility
Thought leadership opportunities
Family-friendly working environment
Interview-process accommodations for accessibility needs