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Scotiabank

Senior AI Solutions Engineer

Dallas, TX, United States

Apply on jobs.scotiabank.com About employer

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Job details

Experience: 7+ years of software engineering, data engineering, platform engineering, or AI/ML solution-delivery experience.
Posting language: English
Posted: Nov 10, 2026

Original job description

Requisition ID: 279025

Salary Range: -

Please 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.

Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.

Purpose

The Senior Software Engineer, AI and Data Solutions, designs and delivers production-grade software, data, and AI-enabled solutions across the organization’s business lines. The role works across application engineering, data processing, platform integration, and AI solution delivery, translating business requirements into secure, scalable, and maintainable software. The engineer contributes to solutions that integrate enterprise applications, data platforms, Customer Data Platforms, APIs, event-driven services, and AI capabilities. They provide technical leadership within delivery squads, guide less-experienced engineers, and help establish reusable engineering patterns for enterprise-scale implementation. This role is expected to independently lead the technical design and implementation of complex solution components while collaborating with architecture, platform, data, security, and product teams.

What You’ll Do

Design, build, test, deploy, and operate scalable software and data solutions using modern engineering practices.
Lead the implementation of complex application components, APIs, microservices, data-processing pipelines, and event-driven integrations.
Translate business and technical requirements into clear solution designs, implementation plans, technical specifications, and engineering tasks.
Build batch and real-time data-processing solutions that ingest, validate, transform, reconcile, enrich, and distribute structured and unstructured data.
Design and implement Customer Data Platform and customer-data capabilities, including profile creation, identity matching, profile unification, segmentation, consent and preference management, and downstream activation.
Contribute to data-quality controls, customer identity crosswalks, matching rules, survivorship logic, lineage, and traceability across source and consuming systems.
Develop and integrate REST APIs, asynchronous services, streaming components, and event-driven workflows.
Contribute to AI-enabled applications, including retrieval-augmented generation, intelligent document processing, conversational experiences, workflow automation, and model-assisted decision support.
Integrate applications with enterprise AI and data services such as Google Cloud Vertex AI, Azure Databricks, vector-search platforms, API management services, and approved large language models.
Apply security, privacy, observability, resilience, and responsible AI controls throughout the software-development lifecycle.
Write unit, integration, contract, performance, and automated regression tests while maintaining appropriate quality and coverage standards.
Lead or participate in architecture, design, code, security, and production-readiness reviews.
Diagnose complex production issues across applications, data pipelines, APIs, cloud services, and distributed systems.
Establish reusable engineering patterns, shared libraries, coding standards, and implementation guidance for delivery teams.
Mentor mid-level and junior engineers through design reviews, pair programming, code reviews, and technical coaching.
Collaborate with product owners, architects, data engineers, AI/ML engineers, platform teams, cybersecurity, risk, and business-domain specialists.
Identify delivery risks, technical debt, data dependencies, and platform limitations, and recommend practical remediation options.
Support proof-of-concept and technical-validation activities, including acceptance criteria, evaluation methods, and production-readiness assessments.

What You’ll Bring

7+ years of software engineering, data engineering, platform engineering, or AI/ML solution-delivery experience.
Demonstrated experience independently designing and delivering complex production software in cloud or enterprise environments.
Strong programming skills in one or more languages such as Java, Python, C#, TypeScript, or Go.
Strong experience with RESTful APIs, microservices, distributed systems, event-driven architecture, relational or NoSQL databases, automated testing, CI/CD pipelines, and cloud-native development.
Hands-on experience building data-processing pipelines using Apache Spark, Databricks, Kafka, Google Cloud Dataflow, Azure Data Factory, or equivalent technologies.
Working knowledge of Customer Data Platform concepts and technologies such as Adobe Experience Platform, Salesforce Data Cloud, Tealium, Twilio Segment, Microsoft Dynamics 365 Customer Insights, Treasure Data, or comparable platforms.
Understanding of customer identity resolution, unified profiles, segmentation, consent, data lineage, data quality, activation, and customer-360 patterns.
Experience implementing data transformations, reconciliation rules, duplicate detection, matching logic, and data-quality controls.
Experience with at least one major cloud platform, preferably Google Cloud Platform or Microsoft Azure.
Familiarity with AI and GenAI application patterns, including prompt orchestration, retrieval-augmented generation, vector search, tool integration, model evaluation, safety controls, and monitoring.
Experience with containerization and orchestration technologies such as Docker and Kubernetes.
Strong understanding of software security, privacy by design, secrets management, access control, logging, monitoring, and production support.
Ability to communicate technical options, risks, and trade-offs to engineering teams, architects, product owners, and business stakeholders.
Experience mentoring engineers and leading technical delivery within an Agile product or platform team. Preferred Qualifications
Bachelor’s or master’s degree in computer science, software engineering, data engineering, information systems, or a related field.
Experience working in financial services or another highly regulated industry.
Experience with Google Cloud Vertex AI, Azure Databricks, Apigee X, Azure API Management, LangGraph, Google ADK, or vector-search technologies.
Cloud, data, security, or software-engineering certifications from Google Cloud, Microsoft Azure, Databricks, or equivalent providers.

Interested?

If 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! At 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.

What's in it for you?

Scotiabank 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.

#Dallas

Location(s): United States : Texas : Dallas

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.

Scotiabank is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by federal, state, or local law.

Apply on jobs.scotiabank.com About employer

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Jobs in the United States