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Senior AI/Data Developer, TD Securities

TD
Toronto, CAN
Full-time
Senior
Onsite
$125,000-$156,000
Discovered 2 weeks ago
PythonFull-stack developmentLarge Language ModelsAgentic AIRetrieval-Augmented GenerationPrompt engineering
Free

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PythonFull-stack developmentLarge Language Models
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Role Overview

TD Securities' Global Research Technology team delivers data, analytics, and AI platforms supporting global research capabilities.

The role focuses on AI-powered applications, data products, and automation that improve analyst productivity and research workflows.

The developer will collaborate with research analysts, business stakeholders, data engineers, and software engineers.

Compensation

  • The stated pay range is $125,000-$156,000 CAD.
  • The role is eligible for discretionary variable compensation based on business and individual performance.

Responsibilities

  • Design AI-powered applications for investment research workflows.
  • Build agentic AI solutions that retrieve, analyze, and synthesize research data.
  • Develop intelligent document processing using LLMs, OCR, NLP, and knowledge retrieval.
  • Create scalable APIs, backend services, and integrations.
  • Build and maintain Databricks and cloud-native data pipelines.
  • Implement RAG architectures, vector search, and modern web applications.
  • Partner with stakeholders on automation and workflow optimization.
  • Ensure security, governance, compliance, and scalability standards.
  • Evaluate emerging AI technologies and contribute to the AI roadmap.

Required Skills and Experience

  • Strong software engineering practices, including testing, CI/CD, and code quality, are required.
  • Deep Python and full-stack development expertise is required.
  • Experience with LLM applications and agentic AI solutions is required.
  • Hands-on experience with RAG, prompt engineering, semantic search, vector databases, and LLM evaluation is required.
  • Production-grade API and backend service experience is required.
  • Practical experience with Databricks or Snowflake and structured and unstructured data is required.
  • Familiarity with Delta Lake, Spark, and modern data platform architectures is listed.

Example Projects

Research report generation and summarization.

Intelligent document review and data extraction.

AI-powered research assistants and company intelligence workflows.

Knowledge management, search, productivity, and workflow automation platforms.

Databricks-based analytics and AI solutions.

Agentic applications integrating data, documents, and internal systems.

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