Senior Developer, Technology Delivery - AI Development

TD Bank; New York (NY); On-site; USD 120,000 - 150,000; Full time

Job summary

TD Bank Group is seeking a Technology Delivery - AI Development role in New York to design, build, test, and support AI-enabled applications across compliance and supervision. The candidate will collaborate with data scientists, architects, and business partners to deliver secure, scalable AI solutions using Python and modern ML frameworks.

The ideal candidate combines software engineering fundamentals with practical AI knowledge, including prompt engineering, embeddings, and cloud AI services.

Qualifications

• Proficiency in Python and AI libraries.
• Experience with generative AI, LLM concepts, prompt engineering, embeddings, vector databases.
• Familiarity with AI development frameworks and cloud AI services.
• Exposure to Azure/AWS/GCP enterprise AI platforms.
• Knowledge of REST APIs, microservices, CI/CD, and DevSecOps practices.

Responsibilities

• Design, develop, test, and maintain AI-enabled applications and APIs.
• Build generative AI capabilities using LLMs, prompt engineering, embeddings, vector search, and agent workflows.
• Prepare and validate data for model development and production inference.
• Integrate AI solutions with enterprise data platforms and cloud services via secure APIs.
• Develop evaluation approaches for model accuracy, bias, explainability, and latency.

Skills

Python

AI Libraries

Prompt Engineering

REST APIs

Cloud AI Services

Education

Bachelor's degree in CS/Software Eng

Tools

Azure AI Foundry

Azure OpenAI Service

Google Vertex AI

Git

Job description

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.

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 escalated 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 eng