Principal Technical Consultant - AI/Cloud Platform Engineering
What you will do
Consulting and delivery leadership
- Work directly with client stakeholders to interpret business and operational challenges and translate them into the right technical solution, whether that is an Azure landing zone, a migration wave, or an agentic platform: which platform fits, what data and governance boundaries, and what the first production candidate should be.
- Lead junior and mid-level consultants on your engagements: set technical direction, review their work, unblock them daily, and develop them into independent delivery owners.
- Shape engagements alongside AHEAD account teams: scope workstreams, define deliverables, estimate effort, and keep delivery on plan as client priorities shift.
- Build and maintain strong client relationships beyond the current statement of work, and identify opportunities to expand AHEAD's footprint through upsell and cross-sell.
- Serve as the senior technical voice in client steering and working sessions, presenting options with tradeoffs and a clear recommendation rather than a menu.
Azure platform engineering
- Lead Azure discovery and assessment engagements: current-state architecture reviews, workload and application inventories, dependency mapping, and cloud readiness assessments that inform landing zone and migration roadmaps.
- Design and deploy enterprise-scale Azure landing zones aligned to the Cloud Adoption Framework: management group and subscription hierarchies, hub-spoke or Virtual WAN networking, policy-as-code guardrails, and identity and RBAC foundations.
- Plan and execute migrations to Azure: workload assessment and right-sizing with Azure Migrate, migration wave sequencing, cutover runbooks, and post-migration validation across compute, storage, databases, and containers.
- Establish hybrid and cross-premises connectivity: ExpressRoute, VPN gateways, and DNS strategies that connect client on-premises environments to Azure.
- Own cost governance and FinOps practices: budgets and alerts, tagging standards, reserved instance and savings plan strategy, and showback or chargeback reporting.
AI agent platform engineering and delivery
- Design and deploy Microsoft Foundry environments for enterprise clients, including network-isolated configurations behind client firewalls: private endpoints, private DNS, subnet delegation, managed identity and RBAC design, and customer-managed keys.
- Stand up Copilot Studio governance for client tenants: environment strategy and environment groups, DLP baselines and connector governance, generative AI settings, channel approval flows, and licensing and capacity guidance.
- Build promotion pipelines in GitHub Actions that move agents from sandbox to production through automated tests, evaluation thresholds, and human approval gates implemented as environment protection rules.
- Implement evaluation and safety frameworks: golden datasets, quality, retrieval, and safety evaluators run in CI, and compensating controls for model paths where platform content filtering does not.
- Develop agents in code with the Foundry SDK (Python) and in Copilot Studio, and establish ALM so agents move between environments by pipeline rather than by hand.
- Advise clients on model selection and placement across the Foundry catalog, including OpenAI and Anthropic models, with data residency, in-region inference, and cost as first-class constraints.
Documentation and enablement
- Author the design documents, as-builts, build guides, technical roadmaps, and runbooks the client operates from after the engagement ends.
- Run workshops, enablement sessions, and office hours for client makers, developers, and administrators.
- Prepare review packages and evidence for client AI governance boards, and keep decision registers current during delivery.
What you bring
- 8+ years in engineering or technical consulting, including 5+ years delivering Azure infrastructure, landing zones, or migrations, and at least 18 months delivering GenAI o