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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer - **Company:** Scotiabank Group - **Location:** Dallas, TX, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** LangGraph Framework, Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, Business Software, Cloud Computing, Cloud Engineering, Software Code Optimization, Encodings, Computer Programming, Data Governance, Data Systems, DevOps, Github, Monitoring of Systems, Python (Programming Language), Machine Learning, OpenAI, Tensorflow, Standard Sql, Software Engineering, Enterprise Data Management, Pinecone, Feature Store, Real Time Systems, Data Ingestion, Pytorch, LangChain, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Apache Spark, Software Security, Deep Learning, Generative AI, Indexer, Agentic-AI, Knowledge Engineering, Web Filtering, Data Lakes, AI Platforms, Kubernetes, Information Technology, Weaviate, Apache Kafka, Cosmos DB, Milvus, Machine Learning Operations, Restful APIs, Terraform, Semantic Kernel, Docker, Databricks, Microservices - **Published:** October 18, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=d7b9c3056320cbd9 ## About the Role * Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or related field., * 5+ years of software engineering experience. * 3+ years of AI/ML engineering experience in production environments. * Experience deploying enterprise-scale AI solutions. * Experience working in highly regulated environments is preferred. Technical Skills Programming * Python (required) * Java or Scala * SQL * REST APIs AI & Machine Learning * Machine Learning model development and deployment * Deep Learning frameworks (PyTorch, TensorFlow) * NLP and LLM technologies * Fine-tuning and model optimization * Evaluation frameworks Generative AI * OpenAI / Azure OpenAI * LangChain, LangGraph, Semantic Kernel * RAG architectures * Vector databases * Agentic AI frameworks * Prompt engineering Cloud & DevOps * Microsoft Azure (preferred) * AWS or GCP experience * Docker * Kubernetes * Terraform * GitHub Actions / Azure DevOps Data Technologies * Databricks * Spark * Kafka * Data Lakes * Vector Stores (Pinecone, Weaviate, Milvus, Cosmos DB) MLOps * MLflow * Model monitoring * CI/CD pipelines * Feature stores * Experiment tracking, * Experience building enterprise AI agents and multi-agent systems. * Experience with AI governance platforms. * Knowledge of financial services, risk, compliance, AML, fraud, or customer analytics. * Experience implementing Responsible AI frameworks. * Microsoft Azure AI certifications or cloud certifications. * Experience leading technical delivery teams. Leadership Competencies * Strong problem-solving and analytical skills. * Ability to translate complex AI concepts into business value. * Excellent communication and stakeholder management skills. ## Description We are seeking an experienced Senior AI Engineer to design, develop, deploy, and scale AI-powered applications across the enterprise. The ideal candidate combines strong software engineering expertise with deep knowledge of machine learning, Generative AI, agentic systems, cloud platforms, and MLOps practices. You will work closely with data scientists, platform engineers, architects, product teams, and business stakeholders to bring AI solutions from concept to production while ensuring security, governance, scalability, and regulatory compliance. What You'll Do AI Solution Development * Design and implement AI/ML and Generative AI solutions for business-critical use cases. * Build intelligent applications leveraging LLMs, RAG architectures, vector databases, and agentic workflows. * Develop APIs, microservices, and reusable AI services for enterprise consumption. * Implement prompt engineering, tool calling, function orchestration, and agent frameworks. Enterprise AI Platform Engineering * Contribute to the design and evolution of Scotiabank's AI platform. * Build scalable AI services on cloud-native architectures. * Enable secure deployment of foundation models and AI agents. * Integrate AI capabilities with enterprise data platforms and business applications. MLOps & AI Operations * Develop CI/CD pipelines for machine learning and Generative AI workloads. * Automate model deployment, monitoring, evaluation, and lifecycle management. * Implement observability, telemetry, model performance tracking, and cost governance. * Ensure AI solutions meet enterprise reliability and security standards. Data & Knowledge Engineering * Build RAG pipelines using structured and unstructured data sources. * Develop data ingestion, embedding, indexing, and retrieval frameworks. * Work with large-scale data platforms including batch and real-time processing systems. * Collaborate with data governance teams to ensure responsible AI practices. AI Governance & Risk Management * Implement AI governance controls, guardrails, content filtering, and responsible AI requirements. * Support regulatory and risk-management processes for AI systems. * Conduct model validations, performance assessments, explainability, and compliance reviews. Stakeholder Collaboration * Partner with business leaders to identify impactful AI opportunities. * Mentor junior engineers and promote engineering best practices. * Collaborate with architecture, security, and infrastructure teams on enterprise initiatives.