At a Glance
- Tasks: Lead AI transformation projects and ensure successful deployment in client enterprises.
- Company: Join a leading tech firm focused on innovative AI solutions.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Be part of a pioneering team defining AI deployment standards across industries.
- Why this job: Shape the future of AI in real-world environments and drive impactful change.
- Qualifications: 10-15 years in engineering with strong AI platform experience and leadership skills.
The predicted salary is between 166590 - 203610 $ per year.
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
- 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.
Role Location Annual Salary Range
British Columbia/Ontario/New Brunswick $142,050 to $292,000
Senior Manager, Forward Deployed AI Engineer employer: Accenture PLC
Accenture Technology is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As part of the Cloud First – Software Development team, you will have access to cutting-edge technologies and opportunities for professional growth while working on impactful AI-enabled solutions for major clients in the transportation sector. With a focus on employee development and a commitment to delivering high-quality applications, Accenture provides a supportive environment where your contributions are valued and recognized.