AI Ops

Full Description

AI OPS

Duration: 12 months

Remote - Y with some trips to office per month

Client name is confidential for now.

Preferred Locations are Windsor, ON or Montreal ideally.

Otherwise could be other locations too since mostly remote.

Minimum 12-15 years total experience with at least 3+ years experience in AI implementation/support

we need a senior AI engineer in Azure who can act as a team lead for our operations team for a AI solution that is live starting in 4 weeks, 1 month KT and then the existing resource ramps down:

Current Responsibilities - Managed Services Technical Lead

Since August, I've been fulfilling the managed services technical lead role for the Document Intelligence Platform.

Below are my thoughts on what the incoming resource will be taking over:

Team Support & Enablement

Training and supporting L2/L3 team members on the Document Intelligence Platform components and architecture

Providing technical guidance on implementations and troubleshooting

Helping the team deploy changes independently from the dev team

Customer-Facing Responsibilities

Primary technical contact for the customer on all technical discussions and architecture questions.

This is from a Managed Services perspective and in addition to the feature development team.

Handling enhancement requests that come through managed services

Training customer technical resources on the platform

Responding to Level 1 and 2 events and writing incident responses

Managing ongoing communication across technical and operational issues

Operational Management

Working with the engagement owner on ticket management processes and backlog prioritization and hygiene.

Leading analysis of performance and accuracy issues

Producing monthly metrics reports and handling ad hoc data requests from the customer

Assigning work to team members and providing practical guidance

Documentation & Monitoring

Maintaining the operational runbook and related documentation

Overseeing the monitoring/alerting setup for the platform

Managing the framework for improving document processing accuracy (training sets, tagging, model optimization)

Note:

Aside from the strictly Managed Services lane, a challenging and interesting part of the job is handling diverse customer requests.

These have been ranging from cost analysis and optimization recommendations to investigating anomalies in document processing, troubleshooting inappropriate content warnings from OpenAI services, and exploring technical possibilities for enhancement requests.

Recommended Background for Incoming Resource

The role requires comfort with Azure architecture discussions, agentic AI/prompt engineering, and hands-on work across Azure Functions, OpenAI services, Cosmos DB, Storage Accounts, Data Factory, plus Node.js, TypeScript, Python, and SQL.

Given the customer-facing nature and operational complexity, someone with managed services experience would be better positioned to identify and address gaps in process, escalation paths, and service delivery that I've likely missed coming from a development background.

The role also benefits from consulting skills around expectation management, translating technical issues for different audiences, and navigating customer organizational dynamics.