Senior AI Forward Deployment Engineer
$143k - $194k per yearUrban Ridge Supplies
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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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#.
- 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.
- 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.
- 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
Job Id: 4n3Pnm/Z9nIIl+1Se01uzKPSH1s+BkPCQC02VCJS4lCrJbaK3h9linlV452e+Dh+5NZjgYXKl6kncMSJbn4p4pADJa51bYHK5w==
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