Forward Deployed AI Engineer - Senior Manager
Quick Summary
time-to-value, reliability, adoption,
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
Requirements
~2 min read- 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 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
Visit us at www.accenture.com
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.
Location & Eligibility
About this job
- Pay per year
- $142,050–$292,000 a year
- 3% above the $210,000 median for Machine Learning Engineer jobs on Jobera (894 salaries).
- Posted
- 7 days ago
Listing Details
- Posted
- October 19, 2026
- First seen
- October 26, 2026
- Last seen
- October 26, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 44%
- Scored at
- October 26, 2026
Signal breakdown
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