751 to 775 of 2,476 Remote Observability Jobs

into CI/CD pipelines. Knowledge of application release management and repository governance. Experience designing and maintaining GitHub Actions pipelines. Exposure to monitoring and observability platforms. Experience working within financial services, government, defence or other highly regulated sectors. If you have a strong background in enterprise application support, automation, platform ...

extend infrastructure using Infrastructure as Code, Docker and GitOps approaches Manage edge devices and on-site collection systems Build and maintain monitoring and observability tools Support integration between hardware, control systems and software platforms Create and maintain technical documentation and operational runbooks What We're Looking For Strong experience ...

solutions, deploy safely, and monitor in production. Develop robust capabilities for partner integrations, data ingestion, and reliable communication. Ensure system resilience, scalability, security, and observability using logs, metrics, and tracing. Collaborate with product managers, data specialists, and engineering teams to deliver incremental business value. What We're Looking For Strong ...

solutions, deploy safely, and monitor in production. Develop robust capabilities for partner integrations, data ingestion, and reliable communication. Ensure system resilience, scalability, security, and observability using logs, metrics, and tracing. Collaborate with product managers, data specialists, and engineering teams to deliver incremental business value. What We're Looking For Strong ...

domains, canonical models, ontologies, semantic layers, and metadata frameworks. Create data architecture roadmaps aligned to business and digital strategy. Drive data governance, lineage, quality, observability, and master data management initiatives. Ensure alignment between enterprise data models and solution architectures. Partner with business and technology stakeholders to define requirements and data ...

Engineering, Platform Engineering, DevOps or production infrastructure operations, together with strong hands-on Python automation skills. You'll also need experience with: Monitoring and observability tools such as Prometheus, Grafana or similar Production incident management and/or on-call environments Automating operational runbooks and repetitive infrastructure processes APIs ...

LLMs beyond simple API integration Your exposure to practical challenges such as: Model behaviour debugging and failure analysis Latency, throughput, and cost optimisation Monitoring, observability, and evaluation frameworks Scaling ML systems in production environments Tech Environment Python (core ML and backend language) PyTorch/modern ML frameworks LLM ecosystem (OpenAI ...

integration and communication patterns via MCP, A2A, OpenAPI, REST, and gRPCBuild production-grade Python APIs and microservices integrating with enterprise systems and AI servicesApply observability and monitoring solutions (Langfuse, Arize, Grafana) to ensure system reliabilityContribute to solution architecture, best engineering practices, and documentationBachelor's/Master's in Computer Science ...

versioned, well-documented APIs that other engineers love to consume. Championing a high-quality engineering culture: testing discipline, peer review, CI/CD excellence, observability, performance and secure coding. Developing hands-on skills with Claude Code , including AI-assisted development patterns, smart refactoring, automated context management and productivity-boosting workflows. ...

cluster lifecycle, workload deployment patterns, and production operations at scale; Experience operating in regulated environments with change control, least privilege, and auditability; Experience with observability and operational measurement; Ability to mentor peers, clarify ambiguous problems, create technical plans, and improve code and review standards; Strong incident resolution and root‐cause ...

solutions with frontier modelsincluding prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design. LLMOps/MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment at scale. Cloud and Model Ecosystems: Direct experience with major model providers (Anthropic, OpenAI, Google) and hyperscaler ...

solutions with frontier modelsincluding prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design. LLMOps/MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment at scale. Cloud and Model Ecosystems: Direct experience with major model providers (Anthropic, OpenAI, Google) and hyperscaler ...

solutions with frontier modelsincluding prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design. LLMOps/MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment at scale. Cloud and Model Ecosystems: Direct experience with major model providers (Anthropic, OpenAI, Google) and hyperscaler ...

solutions with frontier modelsincluding prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design. LLMOps/MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment at scale. Cloud and Model Ecosystems: Direct experience with major model providers (Anthropic, OpenAI, Google) and hyperscaler ...

solutions with frontier modelsincluding prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design. LLMOps/MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment at scale. Cloud and Model Ecosystems: Direct experience with major model providers (Anthropic, OpenAI, Google) and hyperscaler ...

solutions with frontier modelsincluding prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design. LLMOps/MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment at scale. Cloud and Model Ecosystems: Direct experience with major model providers (Anthropic, OpenAI, Google) and hyperscaler ...

solutions with frontier modelsincluding prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design. LLMOps/MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment at scale. Cloud and Model Ecosystems: Direct experience with major model providers (Anthropic, OpenAI, Google) and hyperscaler ...

solutions with frontier modelsincluding prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design. LLMOps/MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment at scale. Cloud and Model Ecosystems: Direct experience with major model providers (Anthropic, OpenAI, Google) and hyperscaler ...

solutions with frontier modelsincluding prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design. LLMOps/MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment at scale. Cloud and Model Ecosystems: Direct experience with major model providers (Anthropic, OpenAI, Google) and hyperscaler ...

solutions with frontier modelsincluding prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design. LLMOps/MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment at scale. Cloud and Model Ecosystems: Direct experience with major model providers (Anthropic, OpenAI, Google) and hyperscaler ...

solutions with frontier modelsincluding prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design. LLMOps/MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment at scale. Cloud and Model Ecosystems: Direct experience with major model providers (Anthropic, OpenAI, Google) and hyperscaler ...

solutions with frontier modelsincluding prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design. LLMOps/MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment at scale. Cloud and Model Ecosystems: Direct experience with major model providers (Anthropic, OpenAI, Google) and hyperscaler ...

solutions with frontier modelsincluding prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design. LLMOps/MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment at scale. Cloud and Model Ecosystems: Direct experience with major model providers (Anthropic, OpenAI, Google) and hyperscaler ...

solutions with frontier modelsincluding prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design. LLMOps/MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment at scale. Cloud and Model Ecosystems: Direct experience with major model providers (Anthropic, OpenAI, Google) and hyperscaler ...

solutions with frontier modelsincluding prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design. LLMOps/MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment at scale. Cloud and Model Ecosystems: Direct experience with major model providers (Anthropic, OpenAI, Google) and hyperscaler ...