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Added 9 mins ago
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Urban Ridge Supplies

Senior AI Forward Deployment Engineer

Toronto, ON, Canada

Pay: Salary Range: $143,000-$194,000 Toronto
Job type: Full-time
Posting language: English · French
Posted: Sep 24, 2026

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Applications open in a new tab.

Original job description

English section of this bilingual listing.

Working with lawyers, varying business services teams, and technology partners, the successful candidate will translate legal and business needs into practical AI agents, workflow automations, and enterprise integrations. The role combines expertise in agent development, data and retrieval architecture, prompt engineering, and legal technology, with a strong focus on accuracy, governance, privacy, security, and client confidentiality.

The successful candidate will work with approved platforms, including Microsoft Copilot and Harvey AI, to accelerate responsible AI adoption and help shape the future of AI-enabled legal services across the firm.

You Will Be Focusing On

Stakeholder Engagement

Partner with lawyers and business leaders to identify, assess, and prioritize AI opportunities.
Lead discovery workshops and solution design sessions, translating business requirements into actionable technical designs.
Communicate complex concepts clearly and advise stakeholders on AI capabilities, risks, and best practices.

AI Agent Development, Prompt Engineering & Automation

Design, build, test, and deploy AI agents, copilots, multi-agent workflows, and automation solutions using approved enterprise platforms.
Create reusable agent templates, prompt libraries, prompting frameworks, and automation patterns.
Implement human-in-the-loop controls, approval processes, and appropriate guardrails.
Maintain practical documentation, playbooks, and guidance that support user adoption and effective prompting.

AI Quality, Evaluation & Responsible Use

Apply grounding, retrieval, validation, citation, testing, and monitoring techniques to improve the accuracy, consistency, and reliability of AI outputs.
Establish quality standards and evaluation frameworks for production AI solutions.
Continuously improve solution performance through prompt optimization, architectural enhancements, and user feedback.
Promote responsible AI practices aligned with firm governance requirements.

Legal Workflow Transformation

Analyze legal and business workflows and design solutions that reduce manual effort and improve service delivery.
Rapidly prototype and deploy high-impact solutions aligned with business needs.

Data, Knowledge & Information Architecture

Design AI solutions that use structured and unstructured enterprise data.
Build Retrieval Augmented Generation (RAG), semantic search, and knowledge retrieval solutions using firm repositories and document management systems.
Develop data pipelines, retrieval architectures, metadata, tagging, and information architecture standards that improve relevance and discoverability.
Collaborate with Information Governance, Records Management, and Knowledge Management teams on enterprise search and knowledge initiatives.

Enterprise Integration & API Development

Co-develop secure, scalable integrations with IT Middleware engineers using REST APIs, Microsoft Graph API, Model Context Protocol (MCP), web services, webhooks, and enterprise integration platforms.
Connect AI solutions with Microsoft 365, legal applications, knowledge management platforms, and other enterprise systems.

Security, Governance & Compliance

Ensure solutions meet firm requirements for security, privacy, data protection, regulatory compliance, ethical walls, information barriers, and client confidentiality.
Collaborate with Information Security, Risk, Compliance, Legal, and operational application teams to embed required controls.
Support AI governance and responsible AI programs.

Continuous Innovation

Monitor developments in artificial intelligence, agentic AI, legal technology, and enterprise automation.
Evaluate emerging technologies, develop proofs of concept and pilots, and recommend adoption opportunities.
Contribute to the firm's AI strategy and roadmap.

Required Experience

What you bring to the role:

Minimum of ten (10) years of experience in software engineering, solutions engineering, automation engineering, data engineering, or a related technical discipline.
Minimum of two (2) years of hands-on experience delivering AI, machine learning, intelligent automation, or generative AI solutions.
Demonstrated experience building and deploying AI agents and agentic workflows in enterprise environments.
Proven ability to work with business stakeholders and deliver solutions from concept through production.

AI, Prompting & Quality Expertise

Deep understanding of agent architectures, orchestration frameworks, multi-agent workflows, and automation platforms.
Strong knowledge of RAG, semantic search, embeddings, enterprise knowledge retrieval, and human-in-the-loop controls.
Expert-level prompt engineering skills, including reusable prompt frameworks, libraries, standards, and end-user enablement.
Experience evaluating and improving AI accuracy, reliability, quality, and business outcomes through grounding, validation, testing, monitoring, and governance.

Data & Integration Skills

Strong background in data engineering and information architecture across structured and unstructured environments.
Experience designing scalable integrations using APIs and services.
Knowledge of REST APIs, Microsoft Graph API, JSON, data modeling and transformation, metadata management, enterprise search technologies, and knowledge repositories.

Technical Skills

Experience with one or more of the following: Microsoft Copilot, Microsoft Copilot Studio, Azure AI Foundry, Azure OpenAI, Harvey AI, Anthropic Claude, LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, Model Context Protocol (MCP), Python, JavaScript, or C#.

Professional Competencies

Exceptional analytical, problem-solving, communication, stakeholder management, and relationship-building skills.
Ability to influence and engage technical and non-technical audiences.
Strong organizational and project management skills, with the ability to manage sensitive information and competing priorities.
Ability to work independently and collaboratively across teams, with strong attention to detail and a commitment to continuous improvement.

Success In This Role Will Be Measured By

Adoption and measurable business impact of production-ready AI solutions and automations.
Improvements in productivity, user experience, manual effort, and process cycle times.
Accuracy, reliability, trustworthiness, and continuous improvement of AI outputs.
Effectiveness of prompt standards, documentation, and user enablement.
Compliance with governance, security, privacy, ethical wall, and client confidentiality requirements.
Contribution to the firm's AI strategy, roadmap, and innovation agenda.

Why Join Our Team

Hybrid work environment
Retirement savings plan with employer contribution
Benefit premiums paid by the firm
Telemedicine services
Wellness matters: Flexible health and wellness allowance that covers much more than gym memberships!
Training and development programs based on your interests and needs

Salary Range: $143,000-$194,000 Toronto

Read the full bilingual original

The Role

We are seeking a Senior AI Forward Deployment Engineer to join the Artificial Intelligence team within Norton Rose Fulbright Canada. This role will design, build, deploy, and optimize secure, scalable AI solutions that improve productivity, service delivery, and access to firm knowledge.

Working with lawyers, varying business services teams, and technology partners, the successful candidate will translate legal and business needs into practical AI agents, workflow automations, and enterprise integrations. The role combines expertise in agent development, data and retrieval architecture, prompt engineering, and legal technology, with a strong focus on accuracy, governance, privacy, security, and client confidentiality.

The successful candidate will work with approved platforms, including Microsoft Copilot and Harvey AI, to accelerate responsible AI adoption and help shape the future of AI-enabled legal services across the firm.

You Will Be Focusing On

Stakeholder Engagement

Partner with lawyers and business leaders to identify, assess, and prioritize AI opportunities.
Lead discovery workshops and solution design sessions, translating business requirements into actionable technical designs.
Communicate complex concepts clearly and advise stakeholders on AI capabilities, risks, and best practices.

AI Agent Development, Prompt Engineering & Automation

Design, build, test, and deploy AI agents, copilots, multi-agent workflows, and automation solutions using approved enterprise platforms.
Create reusable agent templates, prompt libraries, prompting frameworks, and automation patterns.
Implement human-in-the-loop controls, approval processes, and appropriate guardrails.
Maintain practical documentation, playbooks, and guidance that support user adoption and effective prompting.

AI Quality, Evaluation & Responsible Use

Apply grounding, retrieval, validation, citation, testing, and monitoring techniques to improve the accuracy, consistency, and reliability of AI outputs.
Establish quality standards and evaluation frameworks for production AI solutions.
Continuously improve solution performance through prompt optimization, architectural enhancements, and user feedback.
Promote responsible AI practices aligned with firm governance requirements.

Legal Workflow Transformation

Analyze legal and business workflows and design solutions that reduce manual effort and improve service delivery.
Develop solutions supporting document drafting, contract review, matter management, legal research, knowledge retrieval, M&A due diligence, and administrative processes.
Rapidly prototype and deploy high-impact solutions aligned with business needs.

Data, Knowledge & Information Architecture

Design AI solutions that use structured and unstructured enterprise data.
Build Retrieval Augmented Generation (RAG), semantic search, and knowledge retrieval solutions using firm repositories and document management systems.
Develop data pipelines, retrieval architectures, metadata, tagging, and information architecture standards that improve relevance and discoverability.
Collaborate with Information Governance, Records Management, and Knowledge Management teams on enterprise search and knowledge initiatives.

Enterprise Integration & API Development

Co-develop secure, scalable integrations with IT Middleware engineers using REST APIs, Microsoft Graph API, Model Context Protocol (MCP), web services, webhooks, and enterprise integration platforms.
Connect AI solutions with Microsoft 365, legal applications, knowledge management platforms, and other enterprise systems.

Security, Governance & Compliance

Ensure solutions meet firm requirements for security, privacy, data protection, regulatory compliance, ethical walls, information barriers, and client confidentiality.
Collaborate with Information Security, Risk, Compliance, Legal, and operational application teams to embed required controls.
Support AI governance and responsible AI programs.

Continuous Innovation

Monitor developments in artificial intelligence, agentic AI, legal technology, and enterprise automation.
Evaluate emerging technologies, develop proofs of concept and pilots, and recommend adoption opportunities.
Contribute to the firm's AI strategy and roadmap.

Required Experience

What you bring to the role:

Minimum of ten (10) years of experience in software engineering, solutions engineering, automation engineering, data engineering, or a related technical discipline.
Minimum of two (2) years of hands-on experience delivering AI, machine learning, intelligent automation, or generative AI solutions.
Demonstrated experience building and deploying AI agents and agentic workflows in enterprise environments.
Proven ability to work with business stakeholders and deliver solutions from concept through production.

AI, Prompting & Quality Expertise

Deep understanding of agent architectures, orchestration frameworks, multi-agent workflows, and automation platforms.
Strong knowledge of RAG, semantic search, embeddings, enterprise knowledge retrieval, and human-in-the-loop controls.
Expert-level prompt engineering skills, including reusable prompt frameworks, libraries, standards, and end-user enablement.
Experience evaluating and improving AI accuracy, reliability, quality, and business outcomes through grounding, validation, testing, monitoring, and governance.

Data & Integration Skills

Strong background in data engineering and information architecture across structured and unstructured environments.
Experience designing scalable integrations using APIs and services.
Knowledge of REST APIs, Microsoft Graph API, JSON, data modeling and transformation, metadata management, enterprise search technologies, and knowledge repositories.

Technical Skills

Experience with one or more of the following: Microsoft Copilot, Microsoft Copilot Studio, Azure AI Foundry, Azure OpenAI, Harvey AI, Anthropic Claude, LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, Model Context Protocol (MCP), Python, JavaScript, or C#.

Professional Competencies

Exceptional analytical, problem-solving, communication, stakeholder management, and relationship-building skills.
Ability to influence and engage technical and non-technical audiences.
Strong organizational and project management skills, with the ability to manage sensitive information and competing priorities.
Ability to work independently and collaboratively across teams, with strong attention to detail and a commitment to continuous improvement.

Success In This Role Will Be Measured By

Adoption and measurable business impact of production-ready AI solutions and automations.
Improvements in productivity, user experience, manual effort, and process cycle times.
Accuracy, reliability, trustworthiness, and continuous improvement of AI outputs.
Effectiveness of prompt standards, documentation, and user enablement.
Compliance with governance, security, privacy, ethical wall, and client confidentiality requirements.
Contribution to the firm's AI strategy, roadmap, and innovation agenda.

Why Join Our Team

Hybrid work environment
Retirement savings plan with employer contribution
Benefit premiums paid by the firm
Telemedicine services
Wellness matters: Flexible health and wellness allowance that covers much more than gym memberships!
Training and development programs based on your interests and needs

Salary Range: $143,000-$194,000 Toronto

Les échelles salariales indiquées reflètent la plage typique pour ce poste dans la région indiquée. Nous reconnaissons que chaque candidat.e apporte un ensemble unique d’expériences et de compétences, et la rémunération finale sera déterminée avec soin en fonction des qualifications individuelles et des facteurs actuels du marché. Veuillez noter que le salaire sera discuté et négocié lors de l’entrevue.

Toronto: $0 - $0

Vous souhaitez vous joindre à un cabinet proactif et moderne où vous vivrez une expérience professionnelle exceptionnelle dans un cadre de travail inclusif et collaboratif? Joignez-vous à nous!

En tant que cabinet d’avocats mondial, nous favorisons une culture fondée sur l’excellence et le service aux clients et prônons la souplesse, le respect, la diversité et la transparence. Nous nous efforçons de créer un environnement inclusif et équitable où chacun·e peut se montrer sous son vrai jour et réaliser son plein potentiel sur le plan professionnel.

Pour plus de détails sur la façon dont nous intégrons la diversité, l’équité et l’inclusion dans toutes nos activités, veuillez cliquer sur le lien suivant : Diversité, équité et inclusion | Canada | Cabinet d'avocats mondial | Norton Rose Fulbright

Si vous souhaitez vous prévaloir de mesures d’adaptation raisonnables au cours du processus de recrutement, veuillez nous l'indiquer lors de votre candidature. Nous communiquerons avec vous pour en discuter.

Veuillez noter que les personnes qui reçoivent une offre d’emploi peuvent être tenues, pendant leur emploi au sein de Norton Rose Fulbright, de faire la preuve des vaccinations recommandées de temps à autre par le gouvernement ou les autorités de santé publique. Norton Rose Fulbright a le devoir d’accommoder les personnes qui ne sont pas en mesure de se faire vacciner pour des motifs protégés. Les candidat·es qui ont besoin d’un accommodement peuvent communiquer avec nous pour en discuter davantage.

Le droit à l’échelle mondiale

nortonrosefulbright.com

Veuillez noter que cet affichage de poste est diffusé afin de pourvoir un poste actuellement vacant.

Job Id: 4n3Pnm/Z9nIIl+1Se01uzKPSH1s+BkPCQC02VCJS4lCrJbaK3h9linlV452e+Dh+5NZjgYXKl6kncMSJbn4p4pADJa51bYHK5w==

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More about this job

Responsibilities

Design, build, and deploy scalable AI agents and automation solutions to improve legal service delivery and firm productivity. Collaborate with stakeholders to identify AI opportunities and ensure solutions meet governance, security, and privacy standards.

Requirements

Requires at least ten years of experience in software or solutions engineering with a minimum of two years specifically in AI, machine learning, or generative AI. Candidates must possess deep expertise in agent architectures, prompt engineering, data integration, and enterprise-level AI deployment.

Skills

AI Agent Development
Prompt Engineering
Automation Design
Retrieval Augmented Generation
Semantic Search
Data Engineering
Information Architecture
API Development
Python
JavaScript
C#
Microsoft Copilot
Azure AI Foundry
Harvey AI
LangChain
Stakeholder Management

Benefits

Retirement savings plan
Employer contribution
Benefit premiums paid by the firm
Telemedicine services
Flexible health and wellness allowance
Training and development programs

Visa sponsorship

Not detected in the job text

Keywords

Artificial Intelligence
Generative AI
AI Agents
Prompt Engineering
RAG
Semantic Search
Automation
Data Engineering
Information Architecture
REST APIs
Microsoft Graph API
Python
JavaScript
C#
Microsoft Copilot
Azure AI Foundry
Harvey AI
LangChain
LangGraph
Semantic Kernel
CrewAI
AutoGen
Model Context Protocol
Legal Technology
Governance
Compliance
Stakeholder Engagement
Enterprise Integration
Machine Learning
Workflow Automation

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