Senior LLMOps Engineer - Kubernetes & AI (Hybrid, Equity)

Valarian Technologies; Greater London; Hybrid; GBP 90,000 - 150,000; Full time

Benefits offered by this job

Equity

Competitive salary

Employer pension contributions

Private health insurance

Hybrid work setup

Gym memberships

Company retreats

Job summary

Valarian Technologies, a frontier AI and sovereign data security company, is seeking an experienced Senior MLOps/LLMOps Engineer to lead deployment, monitoring, and orchestration of production LLM applications within a large Kubernetes environment. You will bridge AI development and production infrastructure, ensuring secure, scalable, multi-step workflows.

You will design end-to-end AI pipelines, implement robust telemetry, and optimize TTFT and throughput while collaborating in a hybrid

Qualifications

• 3+ years of experience in MLOps, LLMOps, Platform Engineering, AI Infrastructure, or SRE focusing on ML workloads.
• Hands-on experience deploying complex containerized apps on Kubernetes (EKS, GKE, AKS, or bare metal) at scale.
• Strong Python skills for backend automation, tooling, and integration development.
• Experience with monitoring/logging tools (Prometheus, Grafana, Datadog, OpenTelemetry) and LLM-specific tracing/evaluation platforms (LangSmith, Langfuse, TruLens).
• Familiarity with CI/CD pipelines (GitHub Actions, GitLab CI, ArgoCD) and IaC tools (Terraform, Pulumi).
• Deep understanding of agentic architectures, prompt chaining, function calling, and multi-agent coordination.

Responsibilities

• Design, deploy, and manage LLM services and agentic AI workloads in high-throughput Kubernetes clusters.
• Automate deployments, scalable inference endpoints, and rollout strategies (blue/green, canary) via CI/CD pipelines.
• Maintain production operation of agentic workflows: multi-step tool execution, state management, multi-agent coordination.
• Triage and resolve issues across AI app logic, orchestration, external APIs, and cloud infrastructure.
• Build end-to-end monitoring and Eval frameworks to measure AI output accuracy, drift, latency, cost, and hallucination.
• Implement trace observability for agent execution paths (prompts, completions, tool calls, steps).
• Monitor and optimize data pipelines, feature stores, vector indexing, and embedding updates.
• Manage resource allocation (GPU/CPU), memory, autoscaling, and cloud spend to optimize TTFT and throughput.

Skills

MLOps / LLMOps

Kubernetes

Python

CI/CD

Telemetry & monitoring

Agentic AI concepts

Tools

Kubernetes

Python

Prometheus

Grafana

Datadog

OpenTelemetry

GitHub Actions

GitLab CI

ArgoCD

Terraform

Pulumi

Job description

Valarian Technologies, a frontier AI and sovereign data security company, is seeking an experienced Senior MLOps/LLMOps Engineer to lead deployment, monitoring, and orchestration of production LLM applications within a large Kubernetes environment. You will bridge AI development and production infrastructure, ensuring secure, scalable, multi-step workflows.

You will design end-to-end AI pipelines, implement robust telemetry, and optimize TTFT and throughput while collaborating in a hybrid