4 days ago
Base Salary
$120k - $150k/yr
Responsibilities
- Design, develop, test, maintain, and support AI-enabled applications, machine learning components, intelligent automation, APIs, and supporting services.
- Build generative AI capabilities using large language models, prompt engineering, embeddings, vector search, retrieval-augmented generation, tool calling, and agent-based workflows.
- Prepare, transform, validate, and manage structured and unstructured data 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 and document evaluations for model accuracy, relevance, robustness, bias, explainability, latency, and cost.
- Implement monitoring, logging, testing, versioning, deployment controls, MLOps practices, and DevSecOps practices across the AI development lifecycle.
- Apply privacy, security, responsible AI, model risk, data governance, and records-management requirements to solution design and delivery.
- Troubleshoot application, data, model, integration, incident, and outage issues while escalating technical risks and dependencies.
- Collaborate with developers, data scientists, quality engineers, business analysts, risk partners, product owners, and other technology stakeholders.
- Perform code reviews, technical documentation, model cards, implementation guides, knowledge-sharing, unit testing, integration testing, and peer coding reviews.
- Perform supported-application and environment administration, including performance monitoring, configuration, backup, authentication, tuning, and service health monitoring.
- Support incident management, impact assessment, internal and external communications, post-production deployments, and continuous improvement activities.
Requirements
- 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.
- Proficiency in Python and practical experience developing applications and integrating models, data services, or AI capabilities through APIs.
- Experience with at least one machine learning or generative AI framework and large language model application patterns.
- Experience with generative AI concepts including prompt engineering, embeddings, vector databases, retrieval-augmented generation, tool calling, and AI agents.
- Exposure to enterprise AI services and model platforms such as Azure AI Foundry, Azure OpenAI Service, Amazon Bedrock, or Google Vertex AI.
- 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, MLOps, model and prompt versioning, and CI/CD automation.
- Experience with cloud platforms, containerized applications, automated testing, CI/CD, or MLOps practices is preferred.
- Awareness of responsible AI principles including fairness, transparency, explainability, privacy, security, human oversight, and appropriate enterprise-data use.
- Strong analytical, problem-solving, written communication, verbal communication, and cross-functional collaboration skills.
- Financial services, compliance, trade surveillance, market abuse monitoring, or capital markets knowledge is an asset but not required.
- Familiarity with Agile delivery methods, cloud technologies, DevOps practices, and secure software development is preferred.
Benefits
- Base salary range of $120,000-$150,000 USD, with potential variable compensation or incentive awards.
- Health and well-being benefits, savings and retirement programs, paid time off including Vacation PTO, Flex PTO, and Holiday PTO.
- Banking benefits and discounts, career development, training, mentoring, recognition programs, and an online learning platform.
- Training and onboarding sessions, regular career and performance conversations, and development support.
- Work location is New York, New York, United States, with a stated 40-hour schedule.
Categories
About TD bank
TD Bank Group provides retail and commercial banking, credit cards, mortgages, wealth management, insurance, and capital-markets services to consumers, businesses, and institutional clients. Headquartered in Toronto and founded in 1955, it operates across Canada and the eastern United States. The company generates revenue from interest income, fees, and trading activities and is publicly traded on the TSX and NYSE under the symbol TD.