Forward Deployed AI Engineer
Role Overview
This is a production engineering role embedded with enterprise client teams, not consulting, project delivery, or research.
The engineer owns outcomes including time-to-value, adoption, reliability, and scalability.
The role bridges AI pilots and scalable enterprise AI capabilities and is part of Accenture’s Reinvention Deployment Engineering pods.
Key Skills for This Role
Full Job Posting
Role overview
This is a production engineering role embedded with enterprise client teams, not consulting, project delivery, or research.
The engineer owns outcomes including time-to-value, adoption, reliability, and scalability.
The role bridges AI pilots and scalable enterprise AI capabilities and is part of Accenture’s Reinvention Deployment Engineering pods.
Key responsibilities
- Lead enterprise AI platform deployments from architecture through adoption across complex, multi-stakeholder client environments.
- Own programme outcomes across concurrent workstreams, including time-to-value, reliability, adoption velocity, and scalability.
- Move ambiguous business problems to working production systems through rapid experimentation.
- Architect and govern solutions spanning identity, data, security, governance, platforms, and multi-system workflows.
- Advise CTO, CFO, and CISO stakeholders on AI reinvention strategy, value architecture, ROI backlogs, use-case prioritization, and adoption roadmaps.
- Create reusable blueprints, patterns, and accelerators; lead architecture sessions, executive workshops, and code-with sessions.
- Codify delivery learnings, failure patterns, and engineering standards for the FDE practice.
Required qualifications
- Bachelor’s degree or college diploma in a related field.
- At least 7 years of cloud-native engineering experience, including APIs, microservices, containerization, and serverless architectures.
- At least 1 year designing and deploying production agentic solutions, including agents, orchestration, context engineering, RAG, or workflows.
- At least 7 years working with AI platforms, including OpenAI, Claude, Vertex AI, or open-source models, and building multi-provider abstraction layers.
- At least 7 years leading software engineering teams, including delivery oversight, resource allocation, and direct-report development.
- Demonstrated end-to-end delivery ownership in client-embedded environments and experience leading enterprise AI deployments.
- Experience managing engineering teams, defining enterprise AI architecture, and engaging senior stakeholders on strategy and investment.
- Experience leading executive workshops, architecture design sessions, or cross-functional technical engagements.
Compensation
- Annual base salary range for British Columbia, Ontario, and New Brunswick is CAD 100,300 to CAD 216,700.
- The stated range is a guideline for full-time employment and may vary with office location, role, skills, and experience; offers may exceed the range.
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