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Program Manager, Carrier Operations & Governance
Twilio
Remote, Canada
- Full-time
- Remote
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Added 1 hour ago
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Accenture

Forward Deployed AI Engineer - Senior Manager

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

Full-time

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Job details

Job type: Full-time
Posting language: English
Posted: Nov 3, 2026

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

Own account-level AI transformation across the client enterprise - from platform selection and architecture through to enterprise-wide adoption and reinvention at scale, leading enterprise AI platform deployments (Anthropic, OpenAI, Microsoft, Google, Salesforce, SAP, or Palantir) across complex, multi-stakeholder client environments and owning the full programme from architecture through adoption and ongoing iteration
Hold full accountability for deployment outcomes at account level: quality, time-to-value, reliability, adoption velocity, scalability, and ROI across multiple concurrent workstreams, with commercial metrics attached - 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

Lead rapid experimentation at pace: drive ambiguous business problems to working production systems in days or weeks across complex enterprise environments through hands-on prototyping, iteration, and deployment of AI-enabled workflows, agents, copilots, and automations into real operational environments
Define enterprise AI architecture standards and governance frameworks across the client organization, spanning identity, data, security, platform layer, multi-platform integration, multi-system workflow integration at programme scale, and AI lifecycle management; architect and govern enterprise AI solutions across the full technology stack, including prompt and workflow design, API integrations and orchestration, enterprise knowledge integration, and privacy considerations; provide technical leadership and best practices for responsible, secure, and scalable AI deployment
Own the relationship with client CTO, CFO, and CISO: shape AI investment strategy, board level narrative, and multi-year reinvention roadmap; build value architecture, ROI backlogs, use case prioritization frameworks, and multi-year AI adoption roadmaps
Codify delivery learnings, failure patterns, and engineering standards into reusable reinvention blueprints, patterns, accelerators, and playbooks that define what enterprise AI reinvention looks like - assets that scale across markets, industries, and the FDE practice globally; grow the FDE practice and enable the next generation of forward deployed engineers
Lead executive workshops, board-level engagements, architecture design sessions, code-with sessions with client engineering and C-suite leadership teams, and cross-practice architecture reviews that shape the client’s AI reinvention trajectory
Work directly with clients and internal teams to understand business problems, shape AI use cases, and define technical solutions from ambiguous or evolving requirements; serve as the technical bridge between product, engineering, data, and business stakeholders, ensuring solutions are technically sound, usable, and aligned with business value
Design and implement end-to-end AI solutions, integrating LLMs and AI services such as OpenAI, Anthropic, and Gemini with enterprise platforms including SAP, ServiceNow, Salesforce, data platforms, and internal systems

At Accenture, we hire the best people and help them become even better through world-class training, career counseling, mentoring and support to help you maintain professional success.

Travel may be required for this role. The amount of travel will vary from 25% to 75% depending on business need and client requirements.

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 8 years of software engineering experience using Java, TypeScript/JavaScript, or Python
Minimum of 8 years of experience integrating APIs and building distributed, production systems

Minimum of 1 year of experience designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments

Minimum of 1 year of hands-on experience applying AI-native and agentic software development practices across the software development lifecycle, including spec-driven development and the use of AI coding agents to accelerate software design, coding, testing, debugging, modernization, documentation, and delivery.
Minimum of 1 years of experience working with AI platforms, including OpenAI, Claude, Vertex AI, or open-source models, with experience working with enterprise AI platforms such as Anthropic, OpenAI, Microsoft, Google, Salesforce, SAP, or Palantir

Experience building abstraction layers to manage multi-provider AI pipelines

10–15 years of experience leading, managing, and developing software engineering teams, including delivery oversight, resource allocation, performance management, development planning, and professional development of direct reports
Minimum of 8 years of experience in client-facing communication and collaboration, including leading technical discussions, workshops, or delivery sessions under ambiguity, with experience leading executive workshops, architecture design sessions, or cross-functional technical engagements
Minimum of 8 years of experience translating high-level business needs into concrete technical designs and implementations in large enterprise-wide organizations or a professional services firm
Demonstrated end-to-end delivery ownership in a client-embedded environment, including experience leading enterprise AI deployments across multi-stakeholder environments

Experience working directly with enterprise clients on AI deployment initiatives

Experience defining enterprise AI architecture standards, including identity, data, security, governance, multi-system integrations, 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, architecture design sessions, 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

and

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.

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More about this job

Responsibilities

Lead enterprise-wide AI transformation and deployment by architecting production-ready systems and driving adoption within complex client environments. Manage executive relationships, define AI strategy, and oversee the full lifecycle of AI-enabled workflows and agentic solutions.

Requirements

Requires 10-15 years of engineering experience with cloud-native systems and a minimum of 8 years in software engineering using Java, TypeScript, or Python. Candidates must have demonstrated experience in leading AI deployments, managing engineering teams, and translating business needs into technical architecture.

Skills

Artificial Intelligence
Cloud-native systems
Software engineering
Java
TypeScript
JavaScript
Python
API integration
Agentic solutions
RAG
Enterprise architecture
Stakeholder management
Strategic planning
Team leadership
Project management
Data governance

Benefits

Training
Career counseling
Mentoring

Visa sponsorship

Not detected in the job text

Keywords

AI Engineer
Cloud-native
Microservices
Containerization
Serverless
LLM
Anthropic
OpenAI
Vertex AI
SAP
Salesforce
Palantir
RAG
Agentic workflows
API
Enterprise AI
Governance
Data architecture
Prompt engineering
Orchestration
Digital core
Strategy
Consulting
Performance management
ROI
Scalability
Reliability
Automation
Copilots

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