• Assist in the design, development, testing, and deployment of AI/ML models and applications • Collaborate with Engineering, IT, and business stakeholders to translate business needs into technical solutions • Build and optimize data pipelines and inference workflows • Develop prototypes and AI-powered applications within cloud environments such as AWS • Work with both structured and unstructured datasets, including text, APIs, and image-based data • Experiment with large language models (LLMs), prompt engineering techniques, and AI APIs • Document code, experiments, and technical findings for team collaboration and knowledge sharing • Participate in code reviews, sprint planning, and technical discussions with the Engineering team • Present project work and findings to technical and business stakeholders • Support additional projects and initiatives as needed across the department

Company Description It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today - ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone. Job Description ROLE DESCRIPTION As a Sr. Delivery Acceleration AI Engineer, you will design, develop, and optimize AI-powered autonomous implementation solutions that transform how ServiceNow Expert Services deliver customer implementations. Working within the Delivery Acceleration team, you'll focus on building and refining AI agents that automate ServiceNow configuration, generate implementation artifacts, and accelerate time-to-deploy-turning what previously required weeks of manual effort into AI-driven delivery that produces production-ready outputs in hours. This role requires deep expertise in prompt engineering, AI agent architecture, and an understanding of enterprise professional services delivery. You'll work directly with autonomous implementation platforms built on large language models to create, test, and refine the AI-driven workflows that generate ServiceNow configurations, user stories, test scripts, and deployment packages for customer engagements. Critically, you must understand the professional services go-to-market motion-how services are scoped, sold, estimated, and delivered-because the AI solutions you build must align with how consultants and sales teams position and execute customer engagements. Your work directly impacts delivery speed, quality, margin, and the customer experience. Success requires balancing technical depth in AI/LLM systems with practical business acumen. You'll operate in a fast-paced sprint cadence where AI capabilities evolve rapidly, requiring continuous experimentation, rigorous quality validation, and close collaboration with solution architects, product managers, and delivery consultants across AMS, EMEA, and APAC+JPN. You will partner closely with the platform administrator who owns operations, adoption, and governance for the AI-powered deal and delivery document generator, ensuring the AI agents and prompt assets you build are deployed, scaled, and governed effectively across the global delivery community. WHAT YOU GET TO DO IN THIS ROLE: Design & Develop AI-Powered Implementation Agents - Architect and build AI agent workflows that autonomously generate ServiceNow configurations, implementation plans, user stories, and test scripts from customer requirements - Develop, test, and iterate sophisticated prompt chains and orchestration patterns that produce consistent, production-quality outputs across ServiceNow product workflows (ITSM, CSM, HRSD, SPM, etc.) - Design multi-step agentic processes that handle complex implementation logic-scope validation, dependency mapping, configuration generation, and quality assurance-with minimal human intervention - Build and maintain prompt libraries, templates, and reusable patterns that encode delivery best practices and Gold Implementation standards into AI agent behavior, partnering with the platform administrator on library structure, versioning, and publication to end users - Partner with AI Architects and Solution Architects to ensure agent outputs align with ServiceNow platform strategy, product direction, and enterprise readiness standards Lead Prompt Engineering & AI Quality Optimization - Serve as a subject matter expert in prompt engineering techniques for large language models, including chain-of-thought reasoning, few-shot learning, structured output generation, and context window optimization - Design and execute systematic prompt evaluation frameworks that measure output accuracy, consistency, completeness, and adherence to ServiceNow implementation standards - Continuously optimize prompt performance through A/B testing, output analysis, and iterative refinement-treating prompts as production code with version control and quality gates, incorporating user feedback and quality-audit signals surfaced by the platform administrator and the champions network - Develop guardrails and validation logic that ensure AI-generated configurations meet enterprise quality standards before being deployed to the Expert Services community - Stay current on evolving platform capabilities and techniques, rapidly incorporating new approaches that improve agent accuracy and efficiency Integrate AI Solutions with Professional Services GTM & Delivery - Understand the full professional services lifecycle-from pre-sales scoping and estimation through delivery execution and go-live-and ensure AI agent capabilities map to real engagement workflows - Design AI solutions that support accurate estimation by providing data on automated vs. manual effort, enabling services sales teams to right-size engagements - Partner with delivery consultants to validate that AI-generated outputs are usable in real customer contexts, incorporating feedback into continuous improvement cycles - Contribute to packaging AI-accelerated delivery into repeatable service offerings that can be positioned and sold by services and license sales teams Build Platform Integrations & Delivery Automation - Integrate AI agent outputs with the ServiceNow platform, customer engagement portals, and internal delivery systems to create seamless end-to-end automation - Design APIs, data pipelines, and integration patterns that connect autonomous implementation tools with estimation systems, resource management platforms, and project tracking tools - Build automated testing and validation workflows that verify AI-generated configurations against ServiceNow best practices and customer requirements before deployment - Collaborate with the implementation platform team to embed AI capabilities into the customer and partner delivery experience - Ensure all integrations meet enterprise security, data governance, and compliance standards - Coordinate with the platform administrator on release management-staging validation, production rollout, and vendor escalation-so new AI capabilities reach users without disrupting platform stability Drive Measurement & Continuous Improvement - Establish quality metrics for AI agent outputs: accuracy rates, rework percentages, time savings, and customer acceptance rates, feeding these signals into the adoption and ROI metrics the platform administrator reports to A&M leadership - Analyze agent performance data to identify improvement opportunities, failure patterns, and expansion use cases - Contribute to the delivery acceleration roadmap by identifying where AI can fill capability gaps or replace manual processes - Document engineering best practices, architectural patterns, and lessons learned to build organizational knowledge - Participate in sprint ceremonies, code reviews, and cross-team collaboration in a two-week sprint cadence with monthly releases Qualifications To be successful in this role you have: - 5+ years of experience in software engineering, AI/ML engineering, or technical consulting in enterprise software environments - 2+ years of hands-on experience with large language models, prompt engineering, and AI agent development-not just using AI tools, but building production systems on top of them - Demonstrated expertise in prompt engineering techniques: chain-of-thought reasoning, structured output generation, few-shot/zero-shot patterns, context window management, and systematic prompt evaluation - Strong understanding of professional services delivery operations: how engagements are scoped, sold, estimated, staffed, and delivered - Experience with API design, system integration, and building data pipelines that connect AI outputs to enterprise workflows - Proficiency in Python, JavaScript/TypeScript, or similar languages used in AI agent development and automation - Understanding of ServiceNow platform architecture, data models, and configuration patterns - Excellent communication skills-ability to translate technical AI capabilities into business impact for non-technical stakeholders - Experience working in agile, sprint-based environments with measurable delivery outcomes Not required but nice to have: - Experience building autonomous implementation or code generation systems that produce production-ready outputs - Background in management consulting or professional services delivery operations - Familiarity with ServiceNow implementation methodology and delivery best practices - Experience with AI agent orchestration frameworks and multi-step workflow automation - Knowledge of AI ethics, output validation, responsible AI practices, and enterprise governance requirements - ServiceNow platform certifications (CSA, CIS, or similar) - Experience with enterprise estimation tools, resource management platforms, or delivery automation systems Additional Information Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license.

• As a Principal AI Engineer at Rula, you will own the AI foundation that determines how generative AI shows up across mental healthcare. • You will operate where architecture, applied research, and real-world clinical constraints meet, designing durable, production-grade systems that power patient engagement and provider workflows at scale. • This is a deeply hands-on role where you will act as a technical multiplier, architecting core platform primitives (RAG, agentic loops) while setting the standard for technical excellence and safety in a regulated environment.

Role Description This job advertisement is to fill an existing vacancy in the CUPE4207-1 (Employee Group). Title of Course: Public Sector Unions Compensation: - Effective September 1, 2026 - $7,887.59 per half course (195 hours nominally) - Effective September 1, 2026 - $15,775.20 per full course (390 hours nominally) Please note: Instructors who are employed in a 2-hour/week lecture, or the equivalent of a 2-hour/week lecture, are responsible for the first hour of seminar/lab in each course. Duties and responsibilities will be in accordance with Article 22.01 of the Collective Agreement. These include: - Scheduled contact time with students - Non-classroom time (preparation of lectures, student consultation, marking and grading, course administration including grade appeals and cases of academic dishonesty) Qualifications - Ph.D or Doctoral candidate with significant university training in the field of labour studies (e.g. course work, thesis focus) - Demonstrated success in university teaching in labour studies (e.g. course evaluations, letters of reference and/or other components of a teaching dossier) - Demonstrated research in labour studies (e.g. publications, conference presentations, community-based projects) - Specialization or prior teaching experience in area advertised Note: This course will be held online and ASY. Requirements - Please include a cover letter and a current resume. - Members with seniority can provide seniority date in the application questionnaire. - All required documentation must be included, including letters of reference and course/performance evaluations. Positions listed on this posting are subject to course enrolments and budgetary approval. As per Article 22.04 of the Collective Agreement: - Members shall not accept any appointment which, taken together with all other appointments at the University, would cause the member to exceed the maximum number of regular hours (i.e., not overtime hours) allowable in a work week under the Employment Standards Act, as amended from time to time. - Applicants that are in excess of the above noted workload limits will not have their applications considered unless they have received prior written approval from the appropriate Dean and the Human Resources Department. The Collective Agreement governs part-time Instructor, Teaching Assistant, Lab Demonstrator, Course Coordinator and Marker-Grader positions at Brock University. The Agreement can be accessed on the Human Resources Web Site - Collective Agreements . Additional Comments Course descriptions can be found on the Undergraduate course calendar website: Undergraduate Course Calendar . Academic terms generally run from: - Fall – September to December - Winter – January to April - Spring – May to July - Summer – July to August *Actual dates can be found on the Timetables available on the Office of the Registrar web page: Timetables . We are committed to offering flexible work arrangements where possible as outlined in our Flexible Work Arrangement Policy. As a student-centered organization, all employees are required to work on campus as needed. Brock University is committed to creating a respectful and equitable workplace. We strive to foster a culture of diversity and inclusion in our work and learning environments. We welcome applications from all qualified individuals and actively encourage applications from: - women - people with disabilities - members of the 2SLGBTQIA+ community - Indigenous Peoples - people who identify as Black, African and/or Caribbean - racialized and/or ethnic and cultural minority groups - other underrepresented demographic groups at Brock and in the Niagara region Brock also recognizes intersectionality and the interconnected identities, histories, and experiences of these aforementioned groups. We are committed to inclusive and barrier-free recruitment, and we accommodate the needs of applicants throughout all stages of the recruitment process, as outlined in our Employment Accommodation Policy and consistent with the requirements of the Ontario Human Rights Code. Please contact talent@brocku.ca if you require a disability-related accommodation so we can ensure your participation needs are met. Brock University does not use AI Technology at any stage of the recruitment process. We appreciate all applications received. Candidates that are selected for an interview will be contacted. Learn more about Brock University by visiting www.brocku.ca .