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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Solutions Engineer - **Company:** Scotiabank Group - **Location:** Dallas, TX, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Java (Programming Language), Adobe Experience Manager, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Application Services, Automation of Tests, Microsoft Azure, Batch Processing, C Sharp (Programming Language), Code Review, Information Systems, Continuous Integration, Customer Data Management, Data Validation, Information Engineering, Data Transformation, Data Normalization, Data Structures, Data Systems, Relational Databases, Software Debugging, Monitoring of Systems, Python (Programming Language), Machine Learning, Microsoft Dynamics, Object-Oriented Software Development, Scrum Methodology, Role-Based Access Control, Regression Testing, Cloud Services, Runbook, Salesforce.Com, Search Technologies, Secure Coding, Software Engineering, SQL Databases, Data Streaming, Systems Integration, Twilio, TypeScript, Openapi, Enterprise Data Management, Data Logging, Data Processing, Google Cloud, Enterprise Software Applications, Retrieval-Augmented Generation, Large Language Models, Apache Spark, Software Troubleshooting, Git, AI Platforms, Kubernetes, Information Technology, Tealium, Apache Kafka, Data Management, Functional Programming, Api Design, Restful APIs, Data Pipelines, User Identification, Databricks, Programming Languages, Microservices - **Published:** November 12, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=9fd62b058557a4a6 ## About the Role * 5+ years of professional software engineering, data engineering, or application-development experience. * Proficiency in at least one programming language such as Java, Python, C#, TypeScript, or Go. * Experience developing and consuming REST APIs. * Working knowledge of object-oriented or functional programming, data structures and algorithms, relational databases and SQL, Git, automated testing, CI/CD, and Agile delivery. * Experience processing data using SQL, Python, Spark, Databricks, Kafka, cloud-native data services, or comparable technologies. * Basic understanding of batch processing, streaming data, data transformation, schema management, data validation, and error handling. * Familiarity with Customer Data Platform or customer-360 concepts, including unified customer profiles, identity resolution, segmentation, consent, and activation. * Exposure to Adobe Experience Platform, Salesforce Data Cloud, Tealium, Twilio Segment, Microsoft Dynamics 365 Customer Insights, Treasure Data, or a comparable enterprise platform is beneficial. * Understanding of API-based and event-driven integration patterns. * Exposure to Google Cloud Platform, Microsoft Azure, Amazon Web Services, or another enterprise cloud environment. * Interest in AI and GenAI application development, including large language models, retrieval-augmented generation, vector search, and AI-assisted automation. * Ability to troubleshoot software and data-processing issues using logs, monitoring tools, test results, and debugging utilities. * Strong communication, collaboration, documentation, and problem-solving skills. * Ability to work effectively with senior engineers, follow established technical patterns, and incorporate design and code-review feedback., * Bachelor's degree in computer science, software engineering, information systems, data engineering, or a related field, or equivalent practical experience. * Experience with cloud data platforms, microservices, containers, Kubernetes, or event-streaming platforms. * Familiarity with data privacy, secure coding, personally identifiable information, role-based access control, and data-retention requirements. * Exposure to financial services, regulated environments, customer-data management, analytics, marketing technology, or digital-channel platforms. * Foundational cloud or data certification from Google Cloud, Microsoft Azure, Databricks, or an equivalent provider. ## Description The AI Solutions Engineer, builds, tests, and supports software and data components used in enterprise applications, customer-data solutions, and AI-enabled workflows. Working within a cross-functional engineering squad, the engineer implements APIs, application services, data pipelines, integrations, automated tests, and production-monitoring capabilities. The role is suited to an engineer who can independently deliver well-defined components and is developing the skills required to lead increasingly complex solution designs. The engineer will gain practical exposure to cloud platforms, data processing, Customer Data Platforms, and enterprise AI technologies while working with Senior, Staff, and Principal engineers. What You'll Do * Develop, test, document, deploy, and maintain software components, application services, APIs, and data-processing workflows. * Implement well-defined technical designs using established enterprise architecture and engineering patterns. * Build batch and streaming data pipelines that collect, validate, transform, enrich, and distribute data. * Support Customer Data Platform and customer-data use cases, including profile ingestion, data normalization and mapping, identity matching, profile enrichment, segmentation, consent processing, and downstream activation. * Develop and maintain integrations between source systems, enterprise data platforms, Customer Data Platforms, AI services, and consuming applications. * Write clean, secure, maintainable code with appropriate unit, integration, and automated regression tests. * Participate in code reviews, technical design sessions, sprint planning, production-readiness reviews, and incident investigations. * Apply established standards for logging, monitoring, error handling, access control, data protection, and operational support. * Assist with data-quality checks, reconciliation controls, duplicate detection, matching rules, and exception-handling workflows. * Contribute to AI-enabled solutions such as document processing, conversational applications, retrieval-augmented generation, workflow automation, and intelligent search. * Use approved AI models, cloud services, SDKs, and APIs under established architecture, security, and responsible AI controls. * Investigate defects and production issues, perform root-cause analysis, and implement corrective actions with guidance from senior engineers. * Maintain technical documentation, runbooks, API specifications, data mappings, testing evidence, and deployment instructions. * Work with product owners, business analysts, data engineers, AI/ML engineers, architects, cybersecurity teams, and quality-engineering teams. * Continuously improve technical knowledge through hands-on delivery, training, experimentation, and feedback from senior engineers.