AI Operations

Job Title

AI Automation - Operations Engineer

Overview

We are hiring an AI Automation Operations Engineer to own operational excellence for our AI & Automation products and AIOps platforms. This role spans end-to-end reliability across infrastructure, application, middleware, and AI/GenAI layers. You will design monitoring and health checks, lead platform upgrades and high‑availability setups, drive stability and incident management, enable product adoption, document production processes, and contribute to pre‑prod testing and release readiness.

Core Responsibilities

Monitoring and Observability

Design and implement comprehensive monitoring, alerting, and health‑check frameworks across infra, app, middleware, and AI/GenAI layers.
Build dashboards and SLO/SLA telemetry using Grafana, Dynatrace, Azure Monitor, Application Insights, Log Analytics, or equivalent.
Define key metrics (availability, latency, error rates, model drift, pipeline throughput) and set automated alerts and escalation paths.
Automate health checks and synthetic transactions for critical user journeys and model inference paths.

Upgrades, High Availability, and Roadmap

Lead platform and product upgrades, including Active‑Active, Active‑Passive, blue/green and canary deployment strategies.
Plan and own upgrade roadmaps in collaboration with Ops, GCC, Engineering, Product, and stakeholders; coordinate maintenance windows and rollback plans.
Validate upgrades in pre‑prod and staging, ensure zero/low downtime cutovers, and document upgrade runbooks.

Stability, Incident and Problem Management

Own incident lifecycle from detection to resolution and RCA; run incident response and post‑mortems.
Drive reliability engineering practices: capacity planning, performance tuning, chaos testing, and resilience patterns.
Implement automation for remediation, runbook execution, and incident mitigation to reduce MTTR.
Maintain SLAs and report availability and reliability metrics to stakeholders.

Enablement and Adoption

Deliver enablement sessions, workshops, and demos to internal teams and customers on how to use AI Automation products.
Create and maintain user manuals, quick start guides, runbooks, and FAQs tailored to operators, developers, and business users.
Act as SME for onboarding, troubleshooting, and best practices for GenAI/LLM usage and safe model operations.

Production Process Control and Documentation

Map and document production processes, data flows, deployment pipelines, and operational dependencies.
Create runbooks, SOPs, and playbooks for routine operations, change management, and emergency procedures.
Establish governance for change approvals, configuration management, and access controls.

Testing and Release Support

Contribute to pre‑prod testing: functional, integration, performance, load, and model validation tests.
Coordinate release readiness with QA, Dev Ops, and engineering; validate CI/CD pipelines and rollback mechanisms.
Support canary and staged rollouts, monitor metrics during releases, and authorize promotion to production.

Cross‑Functional Collaboration and Vendor Management

Work closely with Dev, SRE, Security, QA, and Product to prioritize reliability work and roadmap items.
Coordinate with cloud providers and third‑party vendors for escalations, upgrades, and capacity planning.
Communicate status and risks to leadership and stakeholders with clear, actionable reports.

Required Technical Skills

Programming and Scripting:
Python or Node.js for automation, monitoring scripts, and tooling.
Monitoring and Observability:
Hands‑on with Grafana, Dynatrace, Azure Monitor, Application Insights, Log Analytics, Prometheus, or equivalent.
Cloud Platforms:

Experience with Azure (preferred) or AWS/GCP; infrastructure provisioning and cost optimization.
Containers and Orchestration:
Docker and Kubernetes (AKS/EKS/GKE) operational experience.
CI/CD and Dev Ops:
Git, Jenkins/Git Hub Actions/Git Lab CI, pipeline troubleshooting and release automation.
ITSM:
Service Now or equivalent for incident, change, and problem management.
Databases and Storage:
Monitoring and basic troubleshooting for SQL and No

SQL systems.
AI/GenAI Operations:
Familiarity with LLMOps/MLOps…