Sr Lead Enterprise AI Engineer

About Northern Trust:

Northern Trust, a Fortune 500 company, is a globally recognized, award-winning financial institution that has been in continuous operation since 1889.

Northern Trust is proud to provide innovative financial services and guidance to the world's most successful individuals, families, and institutions by remaining true to our enduring principles of service, expertise, and integrity. With more than 130 years of financial experience and over 22,000 partners, we serve the world's most sophisticated clients using leading technology and exceptional service.

The Enterprise AI team at Northern Trust performs data science research and develops custom prototypes to problems that 1) are not adequately addressed by available commercial solutions, 2) enhance the customer and/or internal partner experience and 3) provide Northern Trust with a competitive advantage. We are at the forefront of rolling out Generative AI solutions and frameworks for the bank from Proof of Concepts, full stack development of solutions and vendor evaluations. We also serve to inspire and empower applied data science practitioners by facilitating high-quality data science education and collaboration within Northern Trust as well as with top universities and research institutions.

As a Senior AI Engineer, you will be a key player in developing, deploying, and maintaining state-of-the-art Generative AI solutions within the Azure cloud environment. Your role will focus on building and refining Large Language Models (LLM) and RAG systems on Azure infrastructure, ensuring they meet business requirements and enterprise-level standards.

As a member on the team, a candidate will be expected to:

• Develop software, typically in Python, to independently acquire data from disparate sources (databases, files, APIs, etc.) and combine them into appropriate training, validation and testing datasets.
• Analyze raw datasets using descriptive statistics, working directly with domain experts to understand the meaning of data fields
• Have a deep understanding of Generative AI and LLMs, evaluation metrics and theory behind LLMs & conversational AI, since Gen AI will be a core part of many solutions being developed at the Bank.
• Be able to explain the full pattern of Retrieval Augmented Generation (RAG) and make recommendations on which specifics technology and techniques to use when building solutions based on this pattern. In most cases the candidate will be developing and integrating Retrieval-Augmented Generation (RAG) systems on Azure cloud.
• Leverage open-source AI software like TensorFlow, PyTorch, HuggingFace, LangChain, AutoGen, LangGraph and LamaIndex for the solution development and evaluation.
• Evaluate various AI frameworks and services for efficacy and make recommendations on their inclusion as standardized tooling for AI development.
• Integrate these tools and software with Azure services for a seamless development and deployment experience.
• IAC and automation - leverage Terraform for automating cloud provisioning of resources and other infrastructure tasks.
• Build unit tests, data quality checks and data pipelines to ensure that algorithms use trusted data.
• Implement CI/CD pipelines using Azure DevOps, ML Ops, Github Actions, TerraForms for the automated deployment of AI solutions.
• Utilize Azure Kubernetes Service (AKS) for managing and scaling containerized AI applications.
• Regularly update and maintain the AI models, ensuring their relevance and effectiveness using Azure Monitory tools.
• Enforce strict security measures and controls in Azure, including network security configurations and identity management, data encryption and privacy.
• Comply with industry standards, best practices and regulations for AI solutions.
• Work across multiple projects in a fluid environment where work is required across the full research lifecycle from forming a hypothesis, acquiring data, and developing ETL-style software to presenting findings.
• Provide guidance to other software development teams as prototypes and frameworks are engineered for full production environments

Have proven experience in:

• IAC and automation concepts with various tools
• Full stack Azure application development
• Security related concepts and controls, particularly in the cloud environment: virtual networks, subnets, private endpoints, authentication mechanisms, identities and role based access.
• Data protection and encryption techniques and tooling such as key vaults, encryption keys, masking and concepts such as BYOK.
• DevOps including CI/CD techniques and tools particularly Azure based and Github repos
• Develop and maintain an understanding of many algorithms across supervised learning, unsupervised learning and time series analysis
• Propose and develop machine learning ensemble methods that exhibit the best out-of-sample characteristics possible given the input dataset
• Utilize expertise in machine learning algorithms to tune algorithms using available hyper-parameters and carefully select feature subsets
• Discover biases or leakage in datasets and ensure that train/test splits reflect realistic expectations of real-world performance
• Run large scale (either in parallel and/or distributed) training and inference jobs on private or public cloud infrastructure
• Present findings to internal and external customers using both data science language (F1 scores, regression error, statistical significance, etc.) as well as business domain specific language gained from experience analyzing the data in scope.
• Plan and execute data science training sessions and hackathons
• Work with external parties (vendors, universities, etc.) to incorporate new techniques and tools into the data science lab.
• Developing open-source software in a collaborative environment, desired but not required.

Tools/Languages required : Python, Common Python libraries (NumPy , Pandas, Sklearn, etc.), Linux based operating systems, and basic development tools (Python IDEs, source control, etc.)

Tools/Languages preferred : Advanced distributed machine learning frameworks (e.g. Keras, TF, etc.), Azure cloud infrastructure.

Education required : Computer Science degree (undergraduate or graduate level) and strong statistical background.

Preferred education : Data Science specific graduate work, Finance sector experience or coursework.

Certification :

• certifications in Azure Security or DevOps are preferred, but not required.
• Azure AI Engineer Associate or equivalent are preferred, but not required.

Salary Range:
$114,500 - 194,700 USD

Salary range is a good faith estimate of base pay. Northern Trust provides a comprehensive benefits package including retirement benefits (401k and pension), health and welfare benefits (medical, dental, vision, spending accounts and disability), paid time off, parental and caregiver leave, life & accident insurance, and other voluntary and well-being benefits. Northern Trust also provides a discretionary bonus program that may include an equity component.

Working with Us:

As a Northern Trust partner, greater achievements await. You will be part of a flexible and collaborative work culture in an organization where financial strength and stability is an asset that emboldens us to explore new ideas.

Movement within the organization is encouraged, senior leaders are accessible, and you can take pride in working for a company committed to assisting the communities we serve! Join a workplace with a greater purpose.

We'd love to learn more about how your interests and experience could be a fit with one of the world's most admired and sustainable companies! Build your career with us and apply today. #MadeForGreater

Reasonable accommodation

Northern Trust is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation for any part of the employment process, please email our HR Service Center at .

We hope you're excited about the role and the opportunity to work with us. We value an inclusive workplace and understand flexibility means different things to different people.

Apply today and talk to us about your flexible working requirements and together we can achieve greater.