Ai Enablement Senior Engineer (Toronto)

Ai Enablement Senior Engineer (Toronto)

25 Sep
|
Electric Mind
|
Toronto

25 Sep

Electric Mind

Toronto

AtElectric Mind,Engineeringis where strategy meets action. Our team helps organizations cut through complexity—aligning business ambition with technology execution to unlock real, lasting change. You'llwork alongside curious, driven people tackling high-impact challenges for everyone from scaling startups to global enterprises. Each engagement is different, pushing you to learn, adapt, and grow.Electric Mind's Technology Practice brings together deep engineeringexpertise, modern delivery disciplines, and pragmatic architectural thinking to help clients execute complex, mission-critical transformation. We design and implement scalable, secure, high-impact technology solutions that accelerate business outcomes.About The RoleSupport the AI Enablement Technical Lead in the delivery and coaching of the AI adoption across multiple client teams. The Senior Engineer mentors technical client team members (Developers, Quality Engineers, ...) on the optimal use of tools and techniques involving AI that can be used to enable the software delivery lifecycle, this will include but not be limited the use of skills, agents, and prompt engineering techniques to improve AI interactions, the u application of those techniques to support the generation of code, tests, review PRs and other technical activities conducted as part of the AI enabled delivery lifecycle .AI Enablement Senior Enginner will be reporting into the AI Enablement Technical Lead and elevate any issues or findings, outside of their remit, that impede or could impede AI adoption, to the AI Enablement Technical Lead.What You'll DoAct as the contact person for coaching and questions related to AI adoption and AI enablement in the software delivery lifecycle, from technical client team members which the team cannot resolve themselves through the training they will have been provided.. This responsibility will cover multiple client teams. The Senior Engineer must be able to:Mentor technical client team member on how to validate plans and code generated by AI, against intended story outcomesCoach client team members on focusing on delivery rather than detouring into AI skills changes mid-flight capturing friction for later skill change iterationsSupport client team members in instilling a strong review ethic across code, tests, PRs and other AI generated artifacts requiring HITL (Human In The Loop) reviews. Guide the teams in focusing reviews on content and alignment with acceptance criteria rather than styleHelp diagnose experiences and environment friction in real usage (skill discovery, workspace confusion, command generation, dependencies, tests, branch and PR flow, IDE/tool timeouts, request limits, CLI setup). Treat environment friction as separate from AI-method friction — surface anything being worked around rather than fixed,



and either help fix it or elevate it so it is not silently absorbed as "AI doesn't work."Support the integration of tooling (scripting, MCP, ...) by client teams needed by client teams to facilitate the automation of activities between AI and existing enterprise solutions (e.G. Jira & Confluence integrations)Support the creation of the AI knowledge base creation and related AI supported reverse-engineering activities as required by various client teamsSupport the setup of the AI enabled project environment (repositories, skills, agents, configuration files, etc) as needed by each client solution's or client team's specific requirements and contextCoach client team technical staff (Developers, Quality Engineers, ...) how to validate that AI-generated output respects each team's engineering constraints, coding guidelines, test requirements, enterprise standards, etcWork with the indicated team members to capture and improve AI skills and agentic capabilities, reinforcing that skills encode team knowledgeEscalate to the AI Enablement Technical Lead when technical decisions, tooling blockers, access, or capacity issues fall outside the role's remit, and surface recurring friction across your assigned client teams rather than solving these in isolationKey DeliverablesGuidance and mentoring for technical client team members (Developers and Quality Engineers mainly)Support deep-dive sessions and story walkthroughs across its assigned client teams whereas these relate to the ability for team to further AI enablementCreation and supporting the creation of guidance for technical personal such as walkthrough notes, step by step job aides etc.Coaching in AI enabling techniques and practices as per the program's standards and approachLogging and sharing/escalating experience and environment/tooling-friction findingsSupport for AI Knowledge-base creation and reverse-engineering through in person assistance or the delviery of guidance artifacts (documentation, job aides, ...)Capture of AI skill improvement requirements across client teams, and collaboration with program team to elicit these improvementsScripting or support of scripting for enterprise tool integration (e.G. Jira, Confluence, ...)Developer-friction pattern reporting across its assigned client teamsWhat You'll BringStrong software delivery experience across various technology stacks using industry best practices (versioning, PR reviews, solution design, code,



...)Understanding of how to apply AI capabilities such as Spec Driven development to support AI enablement of the Software Delivery LifecycleAbility to run practical, hands‐on enablement sessions with technical personnel, and support client team members in running the sameFamiliarity with AI‐assisted coding tools, agentic IDE workflows, skills, model behaviour, and common AI failure modesAbility to diagnose friction across setup, workspace structure, command execution, dependencies, tests, and source‐control flows, and to distinguish environment friction from AI frictionWorking knowledge of AI‐assisted Quality Engineering methods(e.G. test generation, execution, defect review)Good communication skills and the ability to coach technical personnel who may be skeptical of AI‐generated output or attached to existing coding habitsEnough architectural and code literacy to distinguish a AI skill/prompting problem from a specification quality, context, setup, or codebase problemFamiliarity with SpecDriven development solutions a plusAbility to Help pods test and validate the story‐development / quick‐dev skill chain against realistic stories, including UI framework, API, and other story flavours as they become availableWorking knowledge of the A.I.D.E FrameworkComfort using AI tools to complete job functionsAbout Electric MindElectric Mind is a fast‐growing, AI‐native advisory and digital engineering firm built for those who want to shape the future, not just watch it happen. We blend premium strategyexpertisewithcutting‐edgeAI‐centric engineering to solve complex, meaningful problems for industry‐leading clients.We pride ourselves on a high‐touch delivery model and a culture that values diverse talent, innovation, and true client partnership — creating an environment where your ideas matter and your impact is visible.Ifyou'relooking for a place where you can grow rapid, collaborate with exceptional teammates, and help build a company scaling its capabilities and global footprint at speed — Electric Mind is the place to ignite your career. The future is bright!For more info on Electric Mind, check out our Careers Page and Instagram.Electric Mind is committed to diversity in the workplace. We are an inclusive employer and welcome and encourage applications from all qualified candidates. Applicants' needs will be accommodated during our recruitment and selection process so please advise us if you require accommodation.We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

📌 Ai Enablement Senior Engineer (Toronto)
🏢 Electric Mind
📍 Toronto

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