Manager, Forward-Deployed AI Engineer — AI Mobilization & Transformation

Mobilizing AI Adoption Through Bespoke Engagements

Embed within business units to identify strategic workflow, productivity, and decision-making opportunities where AI can create measurable value.

Lead AI Transformation Engagements that combine discovery, solution design, implementation, and capability building.

Create high-impact use cases that serve as showcase examples for broader organizational adoption.

Translate business challenges into practical applications of AI, agents, and multi-agent orchestration.

Create reusable playbooks, patterns, and training assets that accelerate adoption across the enterprise.

Partner with business leaders to demonstrate measurable outcomes and establish local AI champions.

Support the identification and delivery of high-value AI opportunities across business functions.

Contribute reusable assets and implementation patterns that accelerate future engagements.

Building While Teaching

Design and deploy production-ready AI assistants, agents, and orchestration frameworks that solve real business problems.

Use each engagement as a live learning environment where business and technical teams learn modern AI practices through delivery.

Coach engineers, analysts, product managers, knowledge workers, and operational teams on AI-first ways of working.

Establish a "train-the-trainer" model that enables local teams to continue scaling capabilities after engagements conclude.

Facilitate hands-on workshops focused on prompt engineering, agent design, workflow automation, Copilot practices, and AI-assisted development.

Develop practitioners capable of independently applying AI tools and techniques within their teams.

Promote knowledge sharing and adoption of established AI best practices.

Advancing Agentic Transformation

Architect and implement solutions leveraging Copilot Studio, Azure AI, agent frameworks, orchestration systems, and enterprise platforms.

Develop multi-agent solutions that automate complex business processes and decision flows.

Introduce modern engineering practices including AI-assisted software development, evaluation frameworks, observability, and governance.

Establish proven reference architectures and patterns that can be replicated across business units.

Help business teams evolve from experimentation to operationalized AI solutions.

Evaluate emerging AI capabilities and assist in translating them into practical business applications.

Capturing and Scaling Organizational Learning

Document emerging patterns, successful use cases, implementation approaches, and lessons learned.

Build an enterprise library of AI-enabled workflows, agents, and transformation stories.

Identify adoption barriers and design interventions that accelerate organizational readiness.

Create a feedback loop between field engagements, engineering teams, and organizational readiness programs.

Create reusable assets, implementation approaches, and best practices from engagements.

Share lessons learned to improve future AI transformation efforts across the organization.