{"id":4038783,"url":"https://alion.io/job/scotiabank-director-ai-solutions-engineering","title":"Director, AI Solutions Engineering","company":{"id":1754303,"name":"Scotiabank","domain":"scotiabank.com","url":"https://alion.io/company/scotiabank-com","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":{"grade":"A","score":100,"open_postings":47,"ghost_share":0,"stale_share":0.043,"repost_share":0.085,"time_to_fill_p50_days":17,"computed_at":"2026-11-10T06:52:35Z"}},"role":"Solutions","role_family":"Solutions","seniority":"head","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Dallas, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":13,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Apache Kafka","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Embeddings","optional":false},{"name":"GCP","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"LLMOps","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Apex","optional":true},{"name":"Google ADK","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangChain","optional":true},{"name":"LangGraph","optional":true},{"name":"MLFlow","optional":true},{"name":"Salesforce Data Cloud","optional":true},{"name":"Twilio","optional":true},{"name":"Vertex AI","optional":true}],"status":"live","first_seen_at":"2026-11-10T21:32:31Z","employer_posted_date":"2026-11-10","last_verified_at":"2026-11-10T21:32:31Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Requisition ID: 279038\nSalary Range: -\nPlease note that the Salary Range shown is a guideline only. Salary offered may vary based on factors, including, but not limited to, the successful candidate’s relevant knowledge, skills, and experience.\nJoin a purpose driven winning team, committed to results, in an inclusive and high-performing culture.\nPurpose\nThe Director, AI Solutions Engineering, is a senior engineering leader responsible for translating priority business opportunities into secure, scalable, production-grade AI solutions. Working in partnership with business lines, product teams, data teams, risk partners, and the enterprise AI platform organization, the Director leads a portfolio of AI use cases from discovery and prioritization through implementation, adoption, and value realization.\nThe role leads cross-functional solution pods, establishes reusable delivery patterns, and ensures predictive AI, generative AI, and agentic solutions are measurable, responsible, reliable, and aligned with enterprise architecture and governance standards. The Director also develops engineering talent and provides hands-on technical leadership across software, data, platform integration, MLOps, and LLMOps.\nThis role reports to the Senior Director level, with accountability for an assigned solution portfolio, delivery teams, and business-line partnerships rather than the overall function-wide strategy.\nWhat You'll Do\nAI Solution Portfolio and Roadmap\nDevelop and manage the roadmap for an assigned portfolio of AI solutions and priority business use cases, aligned with enterprise AI strategy, intake, funding, governance, and platform direction.\nPartner with business and technology leaders to identify, assess, and prioritize high-value opportunities such as GenAI assistants, intelligent document processing, agentic workflows, decision support, personalization, and risk-signal generation.\nTranslate business objectives into practical delivery plans with clear scope, data dependencies, architectural decisions, control requirements, adoption measures, and expected business outcomes.\nMaintain solution blueprints and reusable implementation patterns that allow other business-line teams to replicate proven approaches.\nHub-and-Spoke Delivery Leadership\nLead cross-functional delivery pods comprising AI and software engineers, product owners, business SMEs, data specialists, platform teams, cybersecurity, architecture, risk, privacy, and compliance partners.\nOwn delivery outcomes for assigned solutions, including technical quality, schedule, risk management, production readiness, adoption, operational performance, and measurable value.\nProvide hands-on engineering enablement through reference implementations, architecture guidance, reusable CI/CD modules, evaluation harnesses, coding standards, and design reviews.\nCreate transparent delivery governance using milestones, dependency tracking, risk registers, service-level objectives, and executive-ready status reporting.\nAI Engineering, MLOps and LLMOps\nOversee design and implementation of predictive AI, GenAI, retrieval-augmented generation, and agentic solutions across cloud-native application and data platforms.\nEnsure MLOps and LLMOps practices cover evaluation, versioning, deployment, monitoring, rollback, drift detection, prompt management, model and tool changes, and production incident response.\nMaintain reusable patterns for APIs, microservices, prompts, embeddings, vector stores, tool integration, runtime orchestration, observability, resilience, and cost management.\nIntegrate AI engineering into the software-development lifecycle and developer toolchain, including source repositories, automated testing, CI/CD, security scanning, and engineering productivity tooling.\nData Processing and Customer Data Solutions\nGuide solution teams in building secure batch and real-time data-processing pipelines that ingest, validate, transform, reconcile, enrich, and distribute structured and unstructured data.\nEnsure AI solutions apply appropriate data-quality, lineage, metadata, retention, access-control, privacy, and observability standards.\nProvide direction for solutions that use Customer Data Platforms and customer-360 capabilities, including identity resolution, unified customer profiles, segmentation, consent and preference management, personalization, and downstream activation.\nPartner with enterprise data and customer-data teams to define integration patterns between operational systems, governed data products, Customer Data Platforms, analytics environments, and AI applications.\nResponsible AI, Security and Risk\nEmbed privacy, data classification, model governance, explainability, evaluation, human oversight, safety, security, and monitoring controls into solution design and delivery.\nEnsure solutions follow enterprise AI intake, architecture, cybersecurity, model-risk, third-party risk, privacy, and production-governance processes.\nOperationalize risk and control requirements through delivery checklists, automated evidence, approval gates, testing standards, and ongoing monitoring rather than documentation-only compliance.\nPromote responsible experimentation while maintaining clear boundaries for sensitive data, regulated decisions, external models, tools, agents, and production access.\nPlatform Partnership, Reuse and Value Realization\nPartner with AI Platform Engineering and enterprise architecture to translate solution demand into platform requirements and improve shared capabilities such as evaluation, guardrails, model routing, feature and embedding stores, vector search, and agent frameworks.\nDrive adoption of enterprise platform services, standard APIs, reusable components, and golden paths to reduce duplication, delivery time, operational risk, and run costs.\nDefine and track KPIs and OKRs for assigned solutions, including cycle time, adoption, quality, reliability, risk posture, productivity, customer or employee outcomes, and return on investment.\nProvide concise portfolio reporting and decision recommendations to business sponsors, CIO organizations, data and AI leadership, risk partners, and executive governance forums.\nPeople Leadership\nLead, coach, and develop a high-performing team of AI solutions engineers and technical leads, setting clear expectations for delivery, engineering excellence, responsible AI, and business partnership.\nBuild workforce and capability plans for the assigned portfolio, including hiring, succession planning, skill development, performance enablement, and deployment of specialists across solution pods.\nFoster an inclusive, accountable engineering culture that encourages constructive challenge, continuous learning, reuse, operational ownership, and evidence-based decision-making.\nContribute to the broader AI engineering community of practice through technical standards, reusable assets, mentoring, and knowledge sharing.\nWhat You'll Bring\n13+ years of experience in software engineering, data engineering, AI/ML engineering, solution architecture, or technology delivery, including at least 5 years leading engineering teams or complex cross-functional delivery.\nDemonstrated success delivering production AI/ML, GenAI, or data-intensive solutions at enterprise scale, preferably in financial services or another regulated industry.\nProven leadership of cross-functional pods delivering measurable business outcomes in partnership with business-line product owners, domain experts, data teams, and technology stakeholders.\nStrong knowledge of GenAI and agentic-system patterns, retrieval and embeddings, vector databases, prompt and policy engineering, model evaluation, guardrails, and MLOps/LLMOps.\nStrong command of cloud-native engineering on Google Cloud Platform, Microsoft Azure, or comparable platforms, including APIs, microservices, event-driven systems, containers, CI/CD, observability, and reliability engineering.\nWorking knowledge of modern data processing using technologies such as SQL, Python, Apache Spark, Databricks, Kafka, Dataflow, or equivalent batch and streaming services.\nWorking knowledge of Customer Data Platform and customer-360 concepts, including profile unification, identity resolution, segmentation, consent, personalization, activation, customer data quality, and lineage.\nExperience establishing reusable solution patterns, reference architectures, engineering standards, and production-readiness practices that improve delivery speed and reliability across multiple teams.\nDemonstrated ability to implement responsible AI, cybersecurity, privacy, data-governance, and model-risk requirements within engineering delivery.\nStrong stakeholder leadership with the ability to influence senior business, technology, data, risk, and compliance partners and align teams around shared outcomes.\nExperience defining and communicating solution value through KPIs, OKRs, adoption measures, reliability indicators, risk metrics, and financial or operational benefits.\nProven ability to attract, coach, develop, and retain engineering talent while building an inclusive and high-accountability team culture.\nPreferred Qualifications\nBachelor’s or master’s degree in computer science, software engineering, data science, information systems, or a related field, or equivalent practical experience.\nExperience delivering AI or customer-data solutions within banking, insurance, capital markets, healthcare, telecommunications, or another highly regulated environment.\nFamiliarity with Google Cloud Vertex AI, Azure Databricks, Apigee X, Azure API Management, LangGraph, Google ADK, MLflow, Kubernetes, and enterprise vector-search technologies.\nExposure to Customer Data Platforms such as Adobe Experience Platform, Salesforce Data Cloud, Tealium, Twilio Segment, Microsoft Dynamics 365 Customer Insights, Treasure Data, or equivalent platforms.\nKnowledge of applicable Canadian regulatory and privacy expectations, including OSFI B-13, OSFI E-23, OSFI B-10, PIPEDA, and Quebec Law 25.\nRelevant cloud, architecture, data, security, or AI certifications from Google Cloud, Microsoft Azure, Databricks, or comparable providers.\nLeadership Attributes\nEnterprise thinking: connects business priorities to reusable solution patterns, data capabilities, platform services, and enterprise standards.\nEngineering excellence: establishes practical golden paths that improve quality, security, reliability, and time-to-production.\nRisk stewardship: embeds fit-for-purpose controls into engineering workflows without creating unnecessary delivery friction.\nTalent leadership: develops strong technical leaders and creates an environment of accountability, inclusion, and continuous improvement.\nResults orientation: ships production solutions, measures adoption and value, and uses operational evidence to continuously improve.\nInterested?\nIf your experience is closely related but doesn’t align perfectly with every qualification, we do encourage you to apply - you might be the right candidate for this or other roles at Scotiabank!\nAt Scotiabank, every employee is empowered to reach their fullest potential, respected for who they are and, embraced for their differences. That’s why we work to grow and diversify talent and engage employees in a performance-oriented culture.\nWhat's in it for you?\nScotiabank wants you to be able to bring your best self to work - and life, every day. With a focus on holistic well-being, our many flexible benefit programs are designed to help support your unique family, financial, physical, mental, and social health needs.\nLocation(s): United States : Texas : Dallas\nScotiabank is a leading bank in the Americas. Guided by our purpose: \"for every future\", we help our customers, their families and their communities achieve success through a broad range of advice, products and services, including personal and commercial banking, wealth management and private banking, corporate and investment banking, and capital markets.\nAt Scotiabank, we val...","description_format":"text","description_chars":12974,"description_truncated":true,"requirements":{"experience_years_min":13,"management_years_min":5,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":["Continuous learning"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Commercial & Retail Banks","Wealth Management & Financial Advisors","Information Security","Investment Banking & M&A Advisory"],"lifecycle":[{"event":"open","at":"2026-11-10T21:32:31Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":17,"reasons":["conf:0","win:early","comp:brand"],"computed_at":"2026-11-10T22:21:15Z"},"pay":null,"html_url":"https://alion.io/job/scotiabank-director-ai-solutions-engineering","json_url":"https://alion.io/job/scotiabank-director-ai-solutions-engineering.json","meta":{"generated_at":"2026-11-10T22:21:15Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":68,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-11T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.1,"usd":0.01,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":1754303},"rest":"https://alion.io/mcp/rest/get_company?id=1754303"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fscotiabank-director-ai-solutions-engineering"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":2,"usd":0.2},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fscotiabank-director-ai-solutions-engineering"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.1,"usd":0.01},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fscotiabank-director-ai-solutions-engineering"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/scotiabank-director-ai-solutions-engineering\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fscotiabank-director-ai-solutions-engineering"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":4038783}},{"tool":"search_jobs","arguments":{"company":"scotiabank.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":4038783},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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