Forward Deployed AI Engineer - Senior Manager

Accenture PLC; Vancouver; Presencial; CAD 142 000 - 292 000; Tempo integral

Resumo da oferta

Accenture PLC is seeking a Forward Deployed AI Engineer who integrates with client teams to operationalize AI at enterprise scale. You will own time-to-value, adoption, reliability, and ROI across the client organization, not just pilot projects.

You will shape corporate AI strategy, define architecture standards, and drive scalable deployment patterns while leading executive workshops and cross-practice reviews with client leadership.

Qualificações

• 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.
• Minimum of 1 year of experience designing and deploying agentic solutions in production environments.
• Minimum of 7 years of experience working with AI platforms such as OpenAI, Claude, Vertex AI or open-source models.
• Experience building abstraction layers to manage multi-provider AI pipelines.
• 10–15 years of experience leading software engineering teams and delivery ownership in client-embedded environments.
• Experience with enterprise AI deployment initiatives and executive stakeholder engagement.

Responsabilidades

• Own account-level AI transformation from platform selection to enterprise-wide adoption at scale.
• Hold full accountability for deployment outcomes: time-to-value, reliability, adoption and ROI.
• Translate executive strategy into production AI systems across the enterprise.
• Define enterprise AI architecture standards and governance across identity, data, security and lifecycle management.
• Own relationships with client CTO, CFO, and CISO on AI investment strategy.
• Codify reusable patterns and playbooks for scalable enterprise AI reinvention.
• Lead executive workshops, board engagements, and cross-practice reviews.

Conhecimentos

Cloud-native systems

APIs

Microservices

Containerization

Serverless architectures

Agentic solutions design

AI platforms experience

End-to-end delivery ownership

Executive stakeholder management

AI deployment in enterprise

Pattern and playbook development

Formação académica

Bachelor’s degree or college diploma

Ferramentas

OpenAI

Claude

Vertex AI

Open-source models

Descrição da oferta de emprego

Role Description

This is not a consulting role. It is not a project delivery role. It is not a research position. A Forward Deployed AI Engineer is a production engineer who works embedded inside a client's enterprise, shoulder to shoulder with their teams, to make complex AI platforms work in real, messy organizational environments. You own outcomes: time-to-value, adoption, reliability, and scalability. Not delivery milestones. Outcomes.

The market is beginning to understand what leading technology companies have demonstrated: AI products fail not because the models are weak but because deployment is broken. The gap between a successful AI pilot and an AI capability that scales is bridged by engineers who can translate platform capability into measurable business value inside a real enterprise environment. That is this role.

Forward Deployed AI Engineers form the execution spine of our Reinvention Deployment Engineering pods. We are building the largest FDE capability in the services industry. The engineers who join at this stage will define what the role looks like at scale and will have access to the hardest enterprise AI problems in the market across every industry.

Key Responsibilities

• Own account-level AI transformation across the client enterprise — from platform selection and architecture through to enterprise-wide adoption and reinvention at scale
• Hold full accountability for deployment outcomes at account level: time-to-value, reliability, adoption, and ROI — directly reported to client executive leadership
• Drive ambiguity to resolution at account scale: translate executive-level strategic intent into production AI systems operating across the enterprise
• Define enterprise AI architecture standards and governance frameworks across the client organization, spanning identity, data, security, multi-platform integration, and AI lifecycle management
• Own the relationship with client CTO, CFO, and CISO: shape AI investment strategy, board level narrative, and multi-year reinvention roadmap
• Codify reusable patterns and playbooks that define what enterprise AI reinvention looks like — assets that scale across markets, industries, and the FDE practice globally
• Lead executive workshops, board-level engagements, and cross-practice architecture reviews that shape the client’s AI reinvention trajectory

Basic Qualifications

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
• Minimum of 1 year of experience designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments
• Minimum of 7 years of experience working with AI platforms, including OpenAI, Claude, Vertex AI, or open-source models
• Experience building abstraction layers to manage multi-provider AI pipelines
• 10–15 years of experience leading software engineering teams, including delivery oversight, resource allocation, and professional development of direct reports
• Demonstrated end-to-end delivery ownership in a client-embedded environment
• Experience working directly with enterprise clients on AI deployment initiatives
• Experience defining enterprise AI architecture standards, including identity, data, security, and AI lifecycle management
• Experience working with executive stakeholders (CTO, CFO, CISO) on AI strategy and investment decisions
• Experience leading executive workshops, board-level engagements, or cross-functional architecture reviews
• Experience developing reusable deployment frameworks or playbooks
• Experience contributing to the development of engineering standards, practice models, or capability frameworks

Compensation

Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation, based on full-time employment, for roles that may be hired as set forth below. The recruiting efforts for this position are intended to fill a brand new position. The base pay range shown below is intended as a guideline to reflect the majority of offers for this role. It does not represent a maximum limit — in some cases, actual compensation may exceed the range where appropriate. Information on benefits is here.

Role Location Annual Salary Range

• British Columbia/Ontario/New Brunswick $142,050 to $292,000