{"id":1243145,"url":"https://alion.io/job/rbc-lead-ai-engineer","title":"Lead AI Engineer","company":{"id":1757835,"name":"Royal Bank of Canada","domain":"rbc.com","url":"https://alion.io/company/rbc-com","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Phenom","truth_index":{"grade":"A","score":100,"open_postings":70,"ghost_share":0.014,"stale_share":0,"repost_share":0.1,"time_to_fill_p50_days":14,"computed_at":"2026-11-01T06:10:25Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Toronto, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":107000,"max_usd":211000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":26},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":".NET","optional":false},{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"C#","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"MVVM","optional":false},{"name":"NLP","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"SOAP","optional":false},{"name":"SQL","optional":false},{"name":"UiPath","optional":false},{"name":"Machine Learning","optional":true},{"name":"PyTorch","optional":true},{"name":"Scikit-learn","optional":true},{"name":"TensorFlow","optional":true}],"status":"live","first_seen_at":"2026-09-18T00:00:00Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-11-01T13:29:12Z","board_verified":true,"closed_at":null,"days_open":44,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":44},"description":"Job Description\nLead AI Engineer\nWhat is the Opportunity?\nWe are seeking an accomplished Lead AI Engineer to design, develop, and implement AI-driven solutions within our software development lifecycle. You will lead enterprise-scale AI integration initiatives, establish best practices, and advance the technical maturity of our engineering organization. This role actively contributes to improving our Agile, Engineering, and DevOps practices.\nThis position demands exceptional problem-solving skills, deep AI expertise, and proficiency in modern development technologies (.NET/C#, Java, Python). You will effectively communicate and collaborate with engineering teams, business stakeholders, and senior management across multiple projects and organizational boundaries.\nRole Level and Responsibilities\nAs a Lead AI Engineer, you are an expert professional with deep technical expertise who contributes to organizational objectives through innovative solutions to complex business challenges. Your primary focus is identifying root causes and implementing solutions to critical business problems while assessing and communicating the technological impact on the business.\nKey Activities\nEvaluate enterprise software packages and AI platforms, recommending solutions to senior management\nLead and mentor colleagues in AI product reviews, pilot projects, and technology adoption\nConduct in-depth analysis of business requirements for large-scale, mission-critical projects\nPerform feasibility studies and translate complex requirements into robust technical designs\nDrive adoption of AI-driven practices across engineering teams\nWhat You'll Do\nAI Engineering & Implementation\nLead the design and development of MCP (Model Context Protocol) servers and tools for seamless AI integration\nDesign and implement AI-driven automation solutions, including LLM-powered automation, prompt engineering, and conversational AI\nDevelop ML model integration solutions and AI orchestration workflows with monitoring and evaluation\nIntegrate UiPath with enterprise AI platforms and APIs\nSupport implementation of agentic automation and advanced AI use cases\nAI/ML Expertise & Governance\nIntegrate LLM APIs and apply advanced prompt engineering techniques\nDesign and maintain AI workflow orchestration systems\nImplement Intelligent Document Processing and NLP solutions\nDevelop model evaluation, tuning, and governance frameworks\nDesign and manage vector databases and RAG (Retrieval-Augmented Generation) systems\nSupport responsible AI practices and governance models\nAI-Driven Software Development Lifecycle (SDLC)\nImplement AI spec-driven development practices for your squad\nContribute to AI/ML solutions that enhance code generation, testing, deployment, and monitoring\nIntegrate AI technologies into existing SDLC workflows and development tooling\nCollaborate on governance and responsible AI implementation\nTechnical Leadership & Collaboration\nLead technology evaluation and assessment for organizational adoption\nCollaborate with enterprise architecture, security, and compliance teams on AI integration\nContribute to technical training and knowledge-sharing initiatives across the organization\nWhat You Need to Succeed\nMust Have\n10+ years of experience building and operating production software systems at scale\n2-4 years of hands-on experience with LLMs and generative AI in production environments\nExpert proficiency in .NET/C#, Java, Python, SQL, Git, and CI/CD pipelines\nDeep knowledge of design patterns (MVC, MVVM), SOA, and architectural concepts; hands-on development experience with Azure Integration Services\nExpert-level expertise in API architecture (REST/SOAP)\nAdvanced working knowledge of agentic AI patterns: tool use, agent orchestration, ReAct, multi-step reasoning, memory and context management\nProven proficiency in LLM API integration, prompt engineering, and RAG systems (vector databases, embeddings, retrieval strategies)\nDemonstrated experience designing and building MCP servers and tools with agent-tool integration frameworks\nCloud platform expertise (AWS, Azure, or GCP), including containers (Docker/Kubernetes) and CI/CD pipelines\nStrong collaboration and communication skills; comfortable with code reviews, design discussions, and pair programming\nAbility to communicate technical decisions clearly to both technical peers and business stakeholders\nUnderstanding of security, data governance, and responsible AI practices\nNice-to-Have\nExperience with agentic automation and advanced AI solutions in production\nOpen-source contributions to automation or AI/ML projects\nMicrosoft Azure certification (Azure Developer Associate or Azure Solutions Architect Expert)\nExperience building and training machine learning models (regression, classification, clustering) using frameworks like Scikit-learn, TensorFlow, or PyTorch\nWhat's In It For You?\nWe thrive on the challenge to be our best, embrace progressive thinking, and work together to deliver trusted solutions that help our clients and communities prosper. We are committed to supporting each other's growth and creating mutual success.\nComprehensive Total Rewards Program including competitive compensation, bonuses, flexible benefits, commissions, and stock options where applicable\nDevelopment-focused leadership committed to your growth through coaching and career opportunities\nOpportunity to make a meaningful, lasting impact on enterprise AI adoption\nDynamic, collaborative, and high-performing team environment\nWorld-class training programs in financial services and emerging technologies\n Job Skills\nApplication Development, Application Integrations, Application Maintenance, Applications Architecture, Detail-Oriented, Enterprise Application Delivery, Group Problem Solving, Programming Languages, Software Development Life Cycle (SDLC), System ApplicationsAdditional Job Details\nAddress:\n180 WELLINGTON ST W:TORONTOCity:\nTorontoCountry:\nCanadaWork hours/week:\n37.5Employment Type:\nFull timePlatform:\nTECHNOLOGY AND OPERATIONSJob Type:\nRegularPay Type:\nSalariedPosted Date:\n2026-08-26Application Deadline:\n2026-10-09Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above\nOur Employment Opportunities\nAt RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.\nJoin our Talent Community\nStay in-the-know about great career opportunities at RBC. Sign up and get customized info on our latest jobs, career tips and Recruitment events that matter to you.\nExpand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com.\nRBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. 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