Forward Deployed AI Engineer - Senior Manager
Role Overview
A production engineering role embedded inside client enterprises to make complex AI platforms work in real organizational environments.
Own outcomes including time-to-value, adoption, reliability, and scalability rather than delivery milestones.
Join Reinvention Deployment Engineering pods working on enterprise AI deployment and scale.
Key Skills for This Role
Full Job Posting
Role overview
A production engineering role embedded inside client enterprises to make complex AI platforms work in real organizational environments.
Own outcomes including time-to-value, adoption, reliability, and scalability rather than delivery milestones.
Join Reinvention Deployment Engineering pods working on enterprise AI deployment and scale.
Key responsibilities
- Own account-level AI transformation from platform selection and architecture through enterprise-wide adoption and reinvention.
- Account for deployment outcomes including time-to-value, reliability, adoption, and ROI; report directly to client executive leadership.
- Translate executive strategy into production AI systems operating across the enterprise.
- Define architecture standards and governance across identity, data, security, multi-platform integration, and AI lifecycle management.
- Manage relationships with client CTO, CFO, and CISO stakeholders; shape investment strategy, board narratives, and multi-year roadmaps.
- Codify reusable enterprise AI patterns and playbooks for use across markets, industries, and the global practice.
- Lead executive workshops, board-level engagements, and cross-practice architecture reviews.
Required qualifications
- Bachelor’s degree or college diploma in a related field.
- 10–15 years of engineering experience with cloud-native systems, including APIs, microservices, containerization, and serverless architectures.
- At least 1 year designing and deploying agentic solutions in production, including agents, orchestration, context engineering, RAG, or workflows.
- At least 7 years working with AI platforms, including OpenAI, Claude, Vertex AI, or open-source models.
- Experience building abstraction layers for multi-provider AI pipelines.
- 10–15 years leading software engineering teams, including delivery oversight, resource allocation, and direct-report development.
- Experience owning end-to-end delivery in client-embedded environments and working on enterprise AI deployment.
- Experience defining enterprise AI architecture standards and working with executive stakeholders on AI strategy and investment.
- Experience leading executive workshops, board-level engagements, or cross-functional architecture reviews.
- Experience developing reusable deployment frameworks or playbooks and contributing to engineering standards or practice models.
Compensation
- The stated annual base salary range for British Columbia, Ontario, and New Brunswick is CAD 142,050 to CAD 292,000.
- Compensation varies by office location, role, skills, and experience; the range is a guideline and offers may exceed it.
- The range is based on full-time employment.
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