Data and AI Engineer
At a glance
Mid-level AI Engineering role at Scotiabank. Toronto · no salary stated · we estimate CA$106,250–CA$167,125.
Scotiabank has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Shape architecture and delivery plans for complex AI, data and software products, from discovery through production
- Design secure GKE services and governed generative AI solutions using patterns such as RAG, vector search and guardrails
- Build scalable Databricks and Spark data products across Lakehouse layers, while setting Python, SQL, testing and CI/CD practices
- Prepare systems for production by addressing performance, security, monitoring, deployment, rollback and incident response
- Guide engineers through design and code reviews, resolve delivery blockers, and align technical decisions with partner teams
What you bring
- A computer science, software engineering or related STEM degree, or equivalent practical experience
- At least four years in software, data, AI/ML or cloud-native engineering, including technical leadership on production systems
- Advanced Python and SQL ability, with strong API development, software design and testing practices
- Practical Databricks, Spark or PySpark experience, including scalable processing and Lakehouse architecture
Who this fits
This mid-level role suits an engineer ready to lead technical design, mentor colleagues and guide production delivery across AI, data and software work. The position is based in Toronto.
From the employer
Requisition ID: 276434
Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.
The Role:
The Data and AI Engineer provides hands on technical expertise across software engineering, data engineering, and AI/ML. This role shapes solution architecture, establishes engineering standards, and leads complex delivery from discovery through production using Databricks/Lakehouse, GKE, cloud-native services, and governed Generative AI patterns.
Is this role right for you? In this role you will:
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Own end-to-end solution design, architecture trade-offs, non-functional requirements, and implementation patterns for complex AI, data, and software products.
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Provide technical expertise across engineers and workstreams; define roadmaps, sequence delivery, and resolve high-impact blockers and dependencies.
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Lead secure cloud-native application design on GKE, including containerized services, APIs, stateless patterns, autoscaling, resilience, and service integration.
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Design governed Generative AI and agentic solutions using LLMs, RAG, embeddings/vector search, memory, orchestration, guardrails, policy controls, evaluation, and human-in-the-loop patterns.
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Lead integration with enterprise AI gateways and model-access services; assess migration impacts and recommend options that minimize rework and operational risk.
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Architect scalable data products and pipelines using Databricks, Spark/PySpark, Delta/Lakehouse, and Medallion patterns across Bronze, Silver, and Gold layers.
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Establish standards for Python, SQL, APIs, testing, code review, CI/CD, observability, documentation, and reusable components.
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Own production readiness, including performance, capacity, availability, security, vulnerability remediation, deployment controls, rollback, monitoring, and incident response.
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Drive AI/ML governance through evaluation criteria, ground-truth datasets, response and override logging, traceability, auditability, and business validation.
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Partner with Architecture, Data Platform, Security, AI Risk, and business stakeholders to secure alignment, communicate risk, and influence target-state decisions.
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Mentor engineers through design reviews, code reviews, and technical coaching, reducing dependency on individual contributors and raising team capability.
Do you have the skills that will enable you to succeed in this role? We'd love to work with you if you have:
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University degree in Computer Science, Software Engineering, Data Science, Engineering, or a related STEM discipline, or equivalent practical experience.
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4+ years of progressive experience in software engineering, data engineering, AI/ML, or cloud-native delivery, including technical leadership on production systems.
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Advanced Python and SQL skills with strong software design, API development, and testing practices.
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Hands-on experience with Databricks, Spark/PySpark, scalable processing, and Lakehouse/Medallion architecture.
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Experience designing and operating distributed cloud-native applications, APIs, and data platforms.
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Experience leading design reviews, resolving complex technical issues, and mentoring engineers.
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Ability to influence architecture, platform, security, risk, business, and delivery stakeholders.
Nice‑to‑Have Qualifications:
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Experience delivering governed AI solutions in banking or another highly regulated industry.
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Experience with enterprise AI gateways, model hubs, MCP-based integrations, agent-to-agent patterns, Kafka, Airflow, or vector/NoSQL databases.
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Experience preparing architecture artifacts and presenting at architecture, security, or risk governance forums.
What's in it for you?
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Diversity, Equity, Inclusion & Allyship - We strive to create an inclusive culture where every employee is empowered to reach their fullest potential, respected for who they are, and are embraced through bias-free practices and inclusive values across Scotiabank. We embrace diversity and provide opportunities for all employee to learn, grow & participate through our various Employee Resource Groups (ERGs) that span across diverse gender identities, ethnicity, race, age, ability & veterans.
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Accessibility and Workplace Accommodations - We value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. Scotiabank continues to locate, remove and prevent barriers so that we can build a diverse and inclusive environment while meeting accessibility requirements.
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Upskilling through online courses, cross-functional development opportunities, and tuition assistance.
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Competitive Rewards program including bonus, flexible vacation, personal, sick days and benefits will start on day one.
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Dynamic Ecosystem - Free tea & coffee, universal washrooms, and lots of space for team collaboration.
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Community Engagement - No matter where you choose to work from; we offer opportunities for community engagement & belonging with our various programs.
Location(s): Canada : Ontario : Toronto
Scotiabank 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.
At Scotiabank, we value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. If you require accommodation (including, but not limited to, an accessible interview site, alternate format documents, ASL Interpreter, or Assistive Technology) during the recruitment and selection process, please let our Recruitment team know. If you require technical assistance, please click here. Candidates must apply directly online to be considered for this role. We thank all applicants for their interest in a career at Scotiabank; however, only those candidates who are selected for an interview will be contacted.