3 days ago
Toronto, Canada +3 moreStaff+
Responsibilities
- Own account-level AI transformation from platform selection and architecture through enterprise adoption, ongoing iteration, and measurable business outcomes.
- Lead production deployment of AI platforms, agents, copilots, workflows, and automations across complex, multi-stakeholder enterprise environments.
- Define enterprise AI architecture standards and governance covering identity, data, security, integrations, privacy, and AI lifecycle management.
- Integrate LLMs and AI services with enterprise platforms including SAP, ServiceNow, Salesforce, data platforms, and internal systems.
- Advise CTO, CFO, CISO, and executive stakeholders on AI investment strategy, ROI, use-case prioritization, and multi-year adoption roadmaps.
- Lead executive workshops, board-level engagements, architecture sessions, code-with sessions, and cross-functional architecture reviews.
- Manage and develop software engineering teams, including delivery oversight, resource allocation, performance management, and professional development.
- Codify delivery learnings into reusable deployment frameworks, blueprints, accelerators, playbooks, engineering standards, and practice models.
Requirements
- Bachelor’s degree or college diploma in a related field.
- 10–15 years of engineering experience with cloud-native systems, APIs, microservices, containerization, and serverless architectures.
- At least 8 years of software engineering experience using Java, TypeScript/JavaScript, or Python.
- At least 8 years of experience integrating APIs and building distributed production systems.
- At least 1 year of experience designing and deploying agentic solutions, including agents, orchestration, context engineering, RAG, and workflows, in production.
- At least 1 year of experience applying AI-native and agentic software development practices across the software development lifecycle, including AI coding agents.
- At least 1 year of experience with AI platforms such as OpenAI, Claude, Vertex AI, or open-source models, plus enterprise AI platforms.
- 10–15 years of experience leading, managing, and developing software engineering teams.
- At least 8 years of client-facing communication and collaboration experience, including technical discussions, workshops, and executive engagements.
- At least 8 years of experience translating business needs into technical designs and implementations in large enterprises or professional services firms.
- Demonstrated end-to-end ownership of client-embedded enterprise AI deployments and experience defining enterprise AI architecture standards.
- Experience working with executive stakeholders on AI strategy and investment decisions and developing reusable deployment frameworks or playbooks.
Benefits
- World-class training, career counseling, mentoring, and support for professional success are provided.
- Travel may be required, varying from 25% to 75% based on business need and client requirements.
- The role is a full-time position with a stated annual salary range for British Columbia, Ontario, and New Brunswick.
Tech Stack
Categories
Forward Deployed
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.