Principal Technical Consultant - AI/Cloud Platform Engineering

AHEAD; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

AHEAD is seeking a Principal Technical Consultant to own Azure platform engineering and AI agent platforms end-to-end at client sites, from assessment to target design, build, delivery pipelines, and handover.

You will lead engagements, mentor consultants, shape scope, manage client relationships, and advocate for optimal architectural choices with cost governance and security considerations.

Qualifications

• 8+ years in engineering or technical consulting.
• 5+ years delivering Azure infrastructure, landing zones, or migrations.
• At least 18 months delivering GenAI or agent systems to production.
• Proven delivery leadership with teams.

Responsibilities

• Lead client engagements and deliver end-to-end Azure engineering work.
• Mentor junior and mid-level consultants on engagements.
• Define scope, deliverables, and estimates with account teams.
• Present options with recommendations in steering sessions.
• Own cost governance and FinOps practices.
• Design and deploy AI agent platforms for enterprise clients.

Skills

Delivery leadership

Azure infrastructure

GenAI / agent systems

Mentoring junior consultants

Architectural framing

Client relationship management

GitHub Actions

Foundry SDK (Python)

Copilot Studio

Azure Migrate

Tools

GitHub Actions

Foundry SDK (Python)

Copilot Studio

Azure Migrate

Job description

AHEAD helps large enterprises assess, design, build, and migrate to the Microsoft Azure platform, and increasingly helps those same enterprises design, build, and run AI agent platforms on top of it. This role sits in the AIC Platform Engineering practice, alongside consultants who lead Azure assessments, landing zone build-outs, and cloud migrations, and specializes that practice's Azure depth toward AI agent platforms. As a Principal Technical Consultant, you own that work end to end at client sites: you assess current state, design the target platform, build it, wire up the delivery pipeline, and leave the client team able to run it without you.

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 apply, 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 apply.
• 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 or agent systems to production.
• Delivery leadership. You have led small consulting or engineering teams on client work: assigning and reviewing work, mentoring junior consultants, and staying accountable for the engagement outcome, not just your own tasks.
• Solution framing. You can take an ambiguous client problem and land it as a concrete architecture