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Accenture

Advises businesses and runs their technology

Forward Deployed AI Engineer – Senior Manager

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeCA$142.1k - CA$292k /yr

About the Job

Requirements

  • A bachelor's degree or college diploma in a related field is required.
  • 10–15 years of engineering experience with cloud-native systems, including APIs, microservices, containerization, and serverless architectures is required.
  • At least 8 years of software engineering experience using Java, TypeScript/JavaScript, or Python is required.
  • At least 8 years of experience integrating APIs and building distributed, production systems is required.
  • At least 1 year of experience designing and deploying agentic solutions, including agents, orchestration, context engineering, retrieval-augmented generation, and workflows, in production environments is required.
  • At least 1 year of hands-on experience applying AI-native and agentic software development practices across the software development lifecycle, including spec-driven development and AI coding agents for software design, coding, testing, debugging, modernization, documentation, and delivery, is required.
  • At least 1 year of experience working with AI platforms, including OpenAI, Claude, Vertex AI, or open-source models, and experience with enterprise AI platforms such as Anthropic, OpenAI, Microsoft, Google, Salesforce, SAP, or Palantir is required.
  • Experience building abstraction layers to manage multi-provider AI pipelines is required.
  • 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, is required.
  • At least 8 years of client-facing communication and collaboration experience, including leading technical discussions, workshops, or delivery sessions under ambiguity, with experience leading executive workshops, architecture design sessions, or cross-functional technical engagements, is required.
  • At least 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 is required.
  • Demonstrated end-to-end delivery ownership in a client-embedded environment, including experience leading enterprise AI deployments across multi-stakeholder environments, is required.
  • Experience working directly with enterprise clients on AI deployment initiatives is required.
  • Experience defining enterprise AI architecture standards, including identity, data, security, governance, multi-system integrations, and AI lifecycle management, is required.
  • Experience working with executive stakeholders, including CTO, CFO, and CISO, on AI strategy and investment decisions is required.
  • Experience leading executive workshops, board-level engagements, architecture design sessions, or cross-functional architecture reviews is required.
  • Experience developing reusable deployment frameworks or playbooks is required.
  • Experience contributing to the development of engineering standards, practice models, or capability frameworks is required.

Responsibilities

  • Own account-level AI transformation across the client enterprise, from platform selection and architecture through enterprise-wide adoption and reinvention at scale; lead enterprise AI platform deployments across complex, multi-stakeholder client environments and own the full programme through ongoing iteration.
  • Hold full accountability for account-level deployment outcomes, including quality, time-to-value, reliability, adoption velocity, scalability, and return on investment across concurrent workstreams, with commercial metrics, and report directly to client executive leadership.
  • Translate executive-level strategic intent into production AI systems operating across the enterprise, driving ambiguity to resolution at account scale.
  • Lead rapid experimentation by taking ambiguous business problems to working production systems in days or weeks through hands-on prototyping, iteration, and deployment of AI-enabled workflows, agents, copilots, and automations.
  • Define enterprise AI architecture standards and governance frameworks across identity, data, security, platform layers, multi-platform and multi-system workflow integration, and AI lifecycle management; architect and govern enterprise AI solutions 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 relationships with client CTO, CFO, and CISO; shape AI investment strategy, board-level narratives, and multi-year reinvention roadmaps; build value architecture, return-on-investment backlogs, use-case prioritization frameworks, and AI adoption roadmaps.
  • Codify delivery learnings, failure patterns, and engineering standards into reusable reinvention blueprints, patterns, accelerators, and playbooks; grow the forward-deployed engineering practice and enable future 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.
  • Work with clients and internal teams to understand business problems, shape AI use cases, and define technical solutions from ambiguous or evolving requirements; bridge product, engineering, data, and business stakeholders to ensure solutions are technically sound, usable, and aligned with business value.
  • Design and implement end-to-end AI solutions integrating large language models and AI services such as OpenAI, Anthropic, and Gemini with enterprise platforms including SAP, ServiceNow, Salesforce, data platforms, and internal systems.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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