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Triunity Software, Inc.

Role: AI Platform DevOps Engineer

Canada

Job type: Contract
Posting language: English
Posted: Sep 30, 2026

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Original job description

Key Responsibilities

Build and operate observability for LLM gateways, model routing, MCP servers, agent runtimes, and AI platform services.
Implement end-to-end telemetry using OpenTelemetry, Langfuse, metrics, logs, and distributed tracing.
Monitor and analyze LLM/agent latency, errors, token usage, model performance, quality, evaluation results, and production behavior.
Develop dashboards, alerts, and reporting for AI reliability, performance, quality, and operational health.
Build AI cost and usage observability, including attribution by application, team, user, model, workflow, and environment across providers such as OpenAI, Anthropic, and Gemini.
Establish observability and evaluation standards for LLM and agentic applications, including traces, prompts, responses, tool calls, evaluations, and regression signals.
Support AI evaluation and monitoring through golden datasets, scoring, prompt/model comparisons, and production quality checks.
Operate AI platform services on Kubernetes using Helm, Kustomize, GitOps, autoscaling, and progressive/zero-downtime deployments.
Implement platform security, access control, secrets management, PII protection, guardrails, and audit logging.

Key Skills

AI/LLM Observability: Langfuse, OpenTelemetry, LLM tracing, AI evaluation
AI Platforms: LLM gateways, model routing, MCP, agentic AI
Cloud/Platform: Kubernetes, Helm, Kustomize, GitOps, APIs
Monitoring: Prometheus, Grafana, Datadog or similar platforms
AI/ML: OpenAI, Anthropic, Gemini, LangChain, LangGraph, CrewAI, Google ADK
Engineering: Python/Java/Go, REST APIs, CI/CD
Security: OAuth2/OIDC, JWT, RBAC, secrets management, PII/AI guardrails

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More about this job

Responsibilities

Build and operate observability, telemetry, dashboards, alerts, and cost attribution for LLM gateways, models, agents, and AI platform services. Operate secure AI platform services on Kubernetes, establish evaluation and monitoring standards, and support reliable deployments and production quality checks.

Requirements

The role calls for experience with LLM observability and evaluation tools, AI platforms and agent frameworks, and cloud-native operations using Kubernetes, Helm, Kustomize, and GitOps. Relevant skills include monitoring platforms, Python, Java or Go, APIs, CI/CD, and security practices such as access control, secrets management, PII protection, and audit logging.

Skills

Langfuse
OpenTelemetry
LLM Observability
LLM Tracing
AI Evaluation
Kubernetes
Helm
Kustomize
GitOps
Prometheus
Grafana
Datadog
Python
Java
Go
OAuth2/OIDC

Visa sponsorship

Not detected in the job text

Keywords

LLM Gateways
Model Routing
MCP Servers
Agent Runtimes
AI Platform Services
OpenTelemetry
Langfuse
Distributed Tracing
Metrics
Logs
LLM Latency
Token Usage
Model Performance
AI Evaluation
Golden Datasets
Prompt Comparisons
Kubernetes
Helm
Kustomize
GitOps
Autoscaling
Progressive Deployments
Prometheus
Grafana
Datadog
OpenAI
Anthropic
Gemini
LangChain
LangGraph

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