Senior Developer, Technology Delivery – AI Development

Work Location :

New York, New York, United States of America

Hours:

40

Line of Business:

Technology Solutions

Pay Detail:

$120,000 - $150,000 USD

TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Job Description:

Preferred Qualifications:

The Technology Delivery – AI Development role is a hands-on development position focused on designing, building, testing, and supporting artificial intelligence and machine learning solutions across the Compliance, Surveillance and Supervision area. Working with senior developers, data scientists, architects, and business partners, the role contributes to generative AI applications, intelligent automation, reusable AI services, data pipelines, APIs, and integrations with vendor and proprietary platforms. The ideal candidate combines software engineering fundamentals with practical knowledge of Python, machine learning frameworks, large language models, retrieval-augmented generation, prompt engineering, cloud AI services, and responsible AI practices to deliver secure, scalable, explainable, and well-governed solutions.

Responsibilities :

• •Design, develop, test, and maintain AI-enabled applications, machine learning components, intelligent automation, APIs, and supporting services.
• •Build and enhance generative AI capabilities using large language models, prompt engineering, retrieval-augmented generation, embeddings, vector search, and agent-based workflows.
• •Prepare, transform, and validate structured and unstructured data used for model development, grounding, evaluation, and production inference.
• •Integrate AI solutions with enterprise applications, data platforms, vendor products, and cloud services through secure APIs and reusable services.
• •Develop evaluation approaches for model accuracy, relevance, robustness, bias, explainability, latency, and cost, and document results for review.
• •Implement monitoring, logging, testing, versioning, and deployment controls across the AI development lifecycle using MLOps and DevSecOps practices.
• •Apply privacy, security, responsible AI, model risk, data governance, and records-management requirements throughout solution design and delivery.
• •Troubleshoot application, data, model, and integration issues and escalate technical risks, limitations, and dependencies in a timely manner.
• •Collaborate with developers, data scientists, quality engineers, business analysts, risk partners, and product owners to translate use cases into production-ready solutions.
• •Contribute to code reviews, technical documentation, model cards, implementation guides, knowledge-sharing sessions, and reusable development standards.
• •Participate in Agile ceremonies, estimation, sprint planning, proofs of concept, and continuous improvement activities.

Required Skills :

• •Proficiency in Python and familiarity with common AI and data libraries.
• •Experience with generative AI and large language model concepts, including prompt engineering, embeddings, vector databases, retrieval-augmented generation, tool calling, and AI agents.
• •Familiarity with AI development frameworks and toolsets.
• •Exposure to enterprise AI services and model platforms such as Azure AI Foundry, Azure OpenAI Service, Amazon Bedrock, Google Vertex AI, or equivalent technologies.
• •Knowledge of RESTful APIs, microservices, Git, SQL, data processing, and software development practices; Java or Spring Boot experience is an asset.
• •Understanding of model evaluation, experimentation, testing, observability, and MLOps concepts, including model and prompt versioning and CI/CD automation.
• •Awareness of responsible AI principles, including fairness, transparency, explainability, privacy, security, human oversight, and appropriate use of enterprise data.
• •Strong analytical and problem-solving skills with the ability to assess model outputs, identify failure modes, and communicate technical limitations.
• •Clear written and verbal communication skills and the ability to collaborate effectively in a cross-functional delivery environment.
• •Familiarity with Agile delivery methods, cloud technologies, DevOps practices, and secure software development is preferred.
• •A continuous learning mindset and interest in applying AI to compliance, trade surveillance, supervision, and capital markets use cases.

Education & Experience:

• •Bachelor's degree in computer science, software engineering, data science, artificial intelligence, information technology, or a related field; equivalent practical experience may be considered.
• •Typically 3-5 years of relevant software development, data engineering, machine learning, or AI solution delivery experience.
• •Practical experience developing applications with Python and integrating models, data services, or AI capabilities through APIs.
• •Experience with at least one machine learning or generative AI framework and exposure to large language model application patterns.
• •Experience with cloud platforms, containerized applications, automated testing, CI/CD, or MLOps practices is preferred.
• •Experience evaluating model outputs and implementing controls for quality, security, privacy, explainability, and responsible AI is an asset.
• •Financial services, compliance, trade surveillance, market abuse monitoring, or capital markets knowledge is an asset but not required.
• •Demonstrated ability to learn emerging technologies, apply feedback, solve technical problems, and communicate effectively with cross-functional teams.

*General Job Description

The IT Senior Developer TDS provides a broad range of system solutions development to business problems through the development and programming of applications / systems.

Depth & Scope:

• •Responsible for analyzing a broad range of business requirements, conducting program / system research and analysis to identify key components for solutions delivery and problem resolution
• •Develops new applications and performs unit / component test for new application development initiatives aligned to business needs and in accordance with technology architecture standards
• •Ensures effective communication of solutions development requirements for respective area and contributes to project plans, estimations, timelines and status updates to support management team / clients on prioritizing new and existing projects against IT requirements and business objectives
• •Informs key stakeholders of any issues that may impact other areas of the project and resolves or escalates issues as required
• •Supports business inquiries and business activities through execution of small enhancements and break / fix implementations (e.g. source code changes)
• •Works with Business Analysts / Systems Analysts, other technology Developers / Solution Designers to ensure the configuration and custom components meet application requirements and performance goals
• •Creates and maintains quality code, ensures defect free programming consistent with standards; provides code maintenance and supports during testing cycles and post-production deployment and participate in reviewing peer coding
• •Adheres to standard security coding practices to ensure application is free of most common coding vulnerabilities
• •Participates in identifying and recommending development / testing solutions / tools in support of project / application obje