26 to 33 of 33 Remote/Hybrid Cost Control Jobs

MustbeSecurityClearedorbeabletoattainit Life on the team Youll be part of a growing IT Operations team where accurate asset data underpins effective decision-making, compliance, and cost control. Working closely with technical teams, service management, and key stakeholders, youll help ensure IT assets are well managed, visible, and delivering valu click ...

role - Hatfield, Milton Keynes, Nottingham Youll be part of a growing IT Operations team where accurate asset data underpins effective decision-making, compliance, and cost control. Working closely with technical teams, service management, and key stakeholders, youll help ensure IT assets are well managed, visible, and delivering value throughout ...

with deployments, reliability, and scalability Managing infrastructure using Terraform Working with Kubernetes Supporting server migrations, networking, and infrastructure changes where needed Helping improve cloud cost control and scalability What we're looking for Around 3+ years' experience in DevOps, Cloud, or Infrastructure Engineering Strong hands-on AWS experience … keen to grow as a DevOps Engineer Bonus (not essential): Background in infrastructure, sysadmin, or network engineering Experience with server migrations or networking Cloud cost optimisation experience Working pattern & package Hybrid working - 5 days onsite for the first 6 months (Then moves to 2 onsite - 3 days remote) Manchester ...

engineers, checking and reviewing code, and setting standards. Ensure all data platform processes; including ingestion, quality, transformation, security, batch management, monitoring, alerting, and cost control are efficient. Design and help build the data platform – ensuring data is processed through semantic layers and can be modelled effectively. Lead changes ...

tools, platforms and services, making informed build-versus-buy decisions Design cloud-native architectures using serverless and PaaS services to enable rapid deployment, cost control and scalability Define lightweight integration approaches connecting AI solutions with enterprise data sources, systems and APIs Establish security, governance and compliance standards ...

bounded autonomy, deterministic fallbacks. Context/session handling (TTL memory), prompt/tool contracts, tool registry hygiene Build production practices around AI: Evals, monitoring, cost controls (token budgets, caching), model routing, prompt versioning, safe rollout Own production health: Logging, metrics, tracing, dashboards, alerting, post-mortems Improve resilience: Rate limiting … flags, safe deployments Work deeply with DevOps on AWS infrastructure, performance, and reliability: Containerised deployments, networking/security boundaries, secrets, scaling, environment management Own cost/performance trade-offs: Cloud cost monitoring, AI cost optimisation, workload tuning, capacity planning Security, Compliance & Customer-Facing Work Build security into ...

Account, Azure Log Analytics, Synapse Analytics, Azure DevOps. You will define the reference architectures and guardrails that enable teams to build secure, scalable, and cost efficient AI capabilities-spanning intelligent document processing, generative AI applications, and retrieval augmented systems integrated with core enterprise platforms. You will collaborate closely with … balance strategic vision with pragmatic delivery, establish engineering standards, and mentor developers while owning architectural decisions and non functional requirements (performance, resilience, security, and cost). Your Responsibilities Define target state Azure AI reference architectures leveraging Azure AI Foundry, Azure OpenAI, and Azure AI Document Intelligence for enterprise ...

/OCR/validation) and integrate with downstream systems (CRM/ERP/ITSM/EDM). Define non-functional requirements (availability, latency, throughput, cost, DR/RTO-RPO) and ensure solutions meet them. Implement identity & access (Entra ID), data isolation, Key Vault secrets, network security (Private Endpoints … e.g., GDPR, ISO controls) and collaborate with risk, legal, and security for approvals. Define MLOps processes for versioning, evaluation, promotion, rollback, and monitoring (latency, cost, drift, hallucination rate, safety events). Instrument observability (logging, tracing, metrics) and error budgets; establish SLIs/SLOs for AI services. Drive FinOps disciplinecapacity ...