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Forward Deployed AI Engineer - Senior Manager

Accenture
Toronto, CAN
Full-time
Mid-Senior
Onsite
CAD 142,050–292,000
Discovered 3 days ago
Forward deployed AI engineeringCloud-native systemsAPIsMicroservicesContainerizationServerless architectures

Full Job Posting

Role description

A production engineer embedded within client enterprises to make complex AI platforms work in real organizational environments.

Own outcomes such as time-to-value, adoption, reliability, and scalability rather than delivery milestones.

The role is presented as engineering work, not consulting, project delivery, or research.

Responsibilities

  • Own account-level AI transformation from platform selection and architecture through enterprise adoption and scaled reinvention.
  • Take accountability for deployment outcomes including time-to-value, reliability, adoption, and ROI, reporting directly to client executive leadership.
  • Translate executive strategic intent into production AI systems operating across the enterprise.
  • Define enterprise AI architecture standards and governance for identity, data, security, multi-platform integration, and AI lifecycle management.
  • Shape AI investment strategy, board-level narratives, and multi-year roadmaps with client CTO, CFO, and CISO stakeholders.
  • 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 cloud-native engineering experience, including APIs, microservices, containerization, and serverless architectures.
  • At least 1 year designing and deploying production agentic solutions involving agents, orchestration, context engineering, RAG, or workflows.
  • At least 7 years working with AI platforms such as 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 professional development of direct reports.
  • End-to-end ownership in a client-embedded environment and direct enterprise client experience on AI deployment initiatives.
  • Experience defining enterprise AI architecture standards, engaging executive stakeholders on strategy and investment, and leading executive or board-level engagements.
  • Experience developing reusable deployment frameworks or playbooks and contributing to engineering standards, practice models, or capability frameworks.

Compensation

  • For full-time employment, the stated annual base pay range for British Columbia, Ontario, and New Brunswick is CAD 142,050–292,000; actual compensation varies and may exceed the range.

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