1 day ago
Toronto, Canada +2 moreSenior
Responsibilities
- Design, build, deploy, and support end-to-end generative AI, LLM, and agentic AI applications for enterprise workflows.
- Develop tool integrations, workflow actions, API connectors, retrieval systems, orchestration components, and human-approval handoffs.
- Create automated tests, evaluations, monitoring, and quality controls for prompts, retrieval, agent behavior, security, latency, cost, and reliability.
- Integrate and customize LLMs, agents, frameworks, enterprise systems, APIs, data platforms, and workflow platforms.
- Implement Responsible AI, privacy, cybersecurity, data governance, auditability, resiliency, and regulatory controls.
- Operationalize LLMOps and AgentOps, including model and prompt lifecycle management, monitoring, incident response, cost controls, and continuous improvement.
- Analyze model, workflow, and business outcome metrics and recommend improvements to quality, safety, performance, and user trust.
- Collaborate with architects, product owners, designers, data and platform engineers, security, legal/privacy, risk, business users, and operations teams.
- Document technical, integration, evaluation, and operational patterns for cross-functional teams.
- Travel may be required.
Requirements
- At least 3 years of experience in AI engineering, machine learning, deep learning, and NLP solutions and applications.
- At least 3 years of experience designing and deploying AI or machine learning solutions using at least one cloud vendor.
- At least 2 years of experience working on engineering teams with programming languages and frameworks such as Python, JavaScript, Java, Spring, or Go, plus expertise in an AI framework such as LangGraph or Semantic Kernel.
- At least 1 year of experience architecting and operationalizing LLM-driven and agentic application architecture patterns.
- Bachelor’s degree or completion of a college diploma in a related field.
- Hands-on experience building generative AI or agentic AI applications with orchestration frameworks, tool or function calling, RAG, APIs, and enterprise integration patterns.
- Production software engineering experience including Python or JavaScript/TypeScript, API development, testing, observability, and secure coding practices.
- Ability to collaborate across product, design, data, cloud, security, legal/privacy, business, and operations teams.
- Familiarity with enterprise workflow automation, event- or message-driven integration, human-in-the-loop design, and cloud application deployment.
- English proficiency is required for regular interaction with English-speaking stakeholders across Canada.
- Preferred experience includes fine-tuning language models, multimodal inputs and outputs, agentic workflows, knowledge graphs, vector databases, tool use, data pipelines, voice/video/text AI platforms, workflow transformation, evaluation datasets, guardrails, prompt governance, cost optimization, production monitoring, demos, discovery sessions, and adoption workshops.
Benefits
- Annual base salary range of $69,450 to $119,450 CAD for roles in British Columbia, Ontario, or New Brunswick.
- Travel may be required.
- Benefits information is provided through Accenture’s benefits resource.
Tech Stack
Categories
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.