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Forward Deployed AI Engineer

  • Calgary, AB, Canada
  • Vancouver, BC, Canada
  • Ottawa, ON, Canada
  • Toronto, ON, Canada

Role Location Annual Salary Range British Columbia/Ontario/New Brunswick $100,300 to $216,700 · Full-time

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Job details

Pay
Role Location Annual Salary Range British Columbia/Ontario/New Brunswick $100,300 to $216,700
Job type
Full-time
Posting language
English
Posted

Original job description

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

  • Lead enterprise AI platform deployments across complex multi-stakeholder client environments - Anthropic, OpenAI, Microsoft, Google, Salesforce, SAP, or Palantir - owning the full programme from architecture through adoption
  • Own programme-level delivery outcomes: time-to-value, reliability, adoption velocity, and scalability across multiple concurrent workstreams, with commercial metrics attached
  • Lead rapid experimentation at pace: drive ambiguous business problems to working production systems in days or weeks across complex enterprise environments
  • Architect and govern enterprise AI solutions across the full technology stack: identity, data, security, governance, platform layer, and multi-system workflow integration at programme scale
  • Shape AI reinvention strategy for client CTO, CFO, and CISO: build value architecture, ROI backlogs, use case prioritization frameworks, and multi-year AI adoption roadmaps
  • Define and publish reusable reinvention blueprints, patterns, and accelerators that scale across multiple client engagements and grow the FDE practice
  • Lead architecture design sessions, executive workshops, and code-with sessions with client engineering and C-suite leadership teams
  • Codify delivery learnings, failure patterns, and engineering standards that shape the FDE practice and enable the next generation of forward deployed engineers

Basic Qualifications

Required qualifications

  • Bachelor’s degree or college diploma in a related field.
  • Minimum of 7 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 with AI platforms (OpenAI, Claude, Vertex AI, or open-source models), including building abstraction layers for multi-provider pipelines
  • Minimum of 7 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 leading enterprise AI deployments across multi-stakeholder environments
  • Experience managing and developing engineering teams, including performance management and development planning
  • Experience working with enterprise AI platforms such as Anthropic, OpenAI, Microsoft, Google, Salesforce, SAP, or Palantir
  • Experience defining enterprise AI architecture across identity, data, security, governance, and multi-system integrations
  • Experience working directly with senior stakeholders (CTO, CFO, CISO) on AI strategy and investment decisions
  • Experience leading executive workshops, architecture design sessions, or cross-functional technical engagements

 and 

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 $100,300 to $216,700

About Accenture

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services - creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.

Visit us at www.accenture.com 

Equal Employment Opportunity Statement

We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.

More about this job

Responsibilities

Lead enterprise AI platform deployments across complex multi-stakeholder environments while owning outcomes like time-to-value, reliability, and scalability. Drive rapid experimentation and architect AI solutions across the full technology stack to deliver measurable business value.

Requirements

Requires a bachelor's degree and at least 7 years of experience in cloud-native systems and AI platform deployment. Candidates must demonstrate leadership in software engineering and experience working directly with senior stakeholders on AI strategy.

Skills

  • Enterprise AI
  • Cloud-native systems
  • Agentic solutions
  • RAG
  • Orchestration
  • Software engineering
  • Architecture design
  • Stakeholder management
  • API development
  • Microservices
  • Containerization
  • Serverless architectures
  • Data governance
  • Security
  • Multi-system integration
  • Strategy consulting

Visa sponsorship

Not detected in the job text

Categories

  • Technology
  • Software
  • Engineering
  • Consulting
  • Data & Analytics

Keywords

  • AI Engineer
  • Cloud-native
  • APIs
  • Microservices
  • Containerization
  • Serverless
  • Agentic solutions
  • RAG
  • Workflows
  • OpenAI
  • Anthropic
  • Vertex AI
  • Enterprise AI
  • Data governance
  • Security
  • Architecture
  • Strategy
  • ROI
  • Stakeholder management
  • Deployment
  • Scalability
  • Reliability
  • Software engineering
  • C-suite
  • Consulting
  • Digital core
  • Innovation
  • Technology stack
  • Identity management
  • Multi-provider pipelines

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