Lead Data Scientist – AI Engineer

William Blair; Chicago (IL); On-site; USD 186,000 - 222,000; Full time

Job summary

William Blair seeks a Lead AI Engineer to join a newly formed AI Innovation Function within the Investment Banking AI & Technology team. You will be embedded with deal teams, understanding workflows, and delivering AI-powered tools with end-to-end accountability.

The role spans data pipelines, LLM orchestration, and Salesforce integrations, with strong engineering standards and security. Responsibilities include building AI agents, orchestrating multi-step applications, and collaborating across

Qualifications

• 5+ years of software engineering with full-stack focus.
• Hands-on with LLMs: prompt engineering, multi-step orchestration.
• Experience deploying multi-agent ecosystems in production.
• Strong ML fundamentals: train, evaluate, deploy models.

Responsibilities

• Design integration layer between Enterprise Claude, Salesforce, and ML models.
• Develop AI agents and multi-step LLM apps for high-value use cases.
• Set engineering standards: CI/CD, testing, documentation.
• Collaborate with deal teams to automate workflows.
• Build data pipelines with Databricks and Dagster for features and models.
• Prototype quickly from banker pain points into PoCs.
• Evaluate and integrate external AI tools via APIs in Salesforce.
• Enforce security and data governance for confidential deals.

Skills

Full-stack development

LLM orchestration

MLOps

Data pipelines

Cloud infrastructure

Tools

Databricks

Dagster

Airflow

Salesforce integration

Azure

Job description

Solutions for Today’s Challenges. Vision for Tomorrow’s Opportunities.

Join William Blair, the Premier Global Partnership.

We are looking for a Lead AI Engineer to join a newly formed AI Innovation Function, part of the Investment Banking AI & Technology team. This is not a back-office engineering role. Inspired by the Forward Deployed Engineer model, you will be embedded directly with deal teams and industry groups—understanding their workflows firsthand, building AI-powered tools that deliver measurable outcomes, and taking end-to-end accountability for what you ship.

You will set the engineering standards for the team: architecture decisions, code quality, testing practices, and deployment patterns. You will work across the full stack—from data pipelines and ML models to LLM orchestration and Salesforce integrations—with the options to choose the right tool for each problem and the discipline to build for longevity.

Responsibilities

• Design and build the integration layer between Enterprise Claude, Salesforce CRM, and our proprietary ML models, creating the orchestration backbone for AI-powered banking workflows.
• Develop AI agents and multi-step LLM applications for high-value use cases: CIP first-draft generation, buyer landscape analysis, intelligent process letter drafting, and deal status automation.
• Set engineering standards for the Innovation Team: code review practices, CI/CD pipelines, testing frameworks, and documentation norms that enable speed without sacrificing reliability.
• Work directly with deal teams and industry/sector groups to understand workflows, identify automation opportunities, and iterate on deployed tools based on real-world banker feedback.
• Build and maintain data pipelines using Databricks and Dagster for feature engineering, model training, and analytics that feed AI capabilities.
• Perform rapid analysis and prototyping—translate a banker’s pain point into a working proof of concept within days, not weeks.
• Evaluate and integrate point solutions (Rogo.ai, Blueflame AI, Fellow.ai) via APIs, ensuring clean data flows and consistent user experiences within Salesforce.
• Implement security and data governance protocols appropriate for confidential deal information.

Qualifications

• 5+ years of software engineering experience with a strong full-stack foundation, including production experience building applications that serve demanding end users.
• Hands-on experience building applications or agents using large language models: prompt engineering, retrieval-augmented generation, multi-step orchestration, tool use, and evaluation frameworks.
• Experience deploying and operating multi-agent ecosystems in production — including reliability engineering, monitoring, failure recovery, and scaling agent infrastructure for enterprise workloads.
• Strong ML fundamentals—ability to train, evaluate, and deploy models, perform exploratory data analysis, and build feature pipelines.
• Rigorous engineering practices: you write tested, reviewed, well-documented code and build systems designed for maintainability, not just demos.
• Familiarity with capital markets, and preferably direct experience in or adjacent to investment banking, private equity, venture capital, or hedge funds.
• Experience with cloud infrastructure (Azure preferred), data platforms (Databricks/Spark), and orchestration tools (Dagster, Airflow, or equivalent).
• Outcome orientation—you measure success by business impact delivered, not features shipped.

Preferred Qualifications

• Experience in a Forward Deployed Engineer, solutions engineer, or embedded technical role where you owned outcomes alongside business stakeholders.
• Prior work with Salesforce APIs, SOQL, or CRM integration patterns.
• Experience architecting production-grade, interconnected multi-agent ecosystems — designing agent coordination patterns, shared tooling layers, and communication protocols across autonomous components.
• Experience building AI tools for financial professionals, including document generation, financial analysis automation, or deal workflow tooling.
• Contributions to engineering culture: mentoring, establishing best practices, or leading technical design reviews in a small-team environment.

A reasonable estimate of the current base salary range at time of posting is below. Base salary does not include other forms of compensation or benefits. Actual base salary within the specified range is based on several factors, including but not limited to applicant's skills, prior relevant experience, specific degrees and certifications, job responsibilities, market considerations and, if applicable, the location of the position.

This role is eligible for either a discretionary annual bonus (based on company, business unit and individual performance) and/or commission-based incentives.

Our featured benefit offerings include medical, dental and vision coverage, employer paid short & long-term disability and life insurance, 401(k), profit sharing, paid time off, Maven family & fertility benefit, parental leave (including adoption, surrogacy, and foster placement), as well as other voluntary benefits.

Salary Range

$186,000—$222,000 USD

About Our Firm

William Blair strives to attract qualified candidates who specialize in investment banking, investment management, private wealth management, and other strategic resource groups. We are committed to empowering our colleagues to deliver client success and engage in our communities. Our firm has delivered trusted advice for nine decades, continuing to deepen our expertise and relationships across asset classes and markets throughout North America, Europe, and Asia. We provide advisory services, strategies, and solutions to meet clients’ evolving needs amid dynamic market conditions and varying industries. What sets us apart is that we are an independent partnership, with colleagues who have unique experiences, perspectives, and backgrounds. We empower our people to bring their best thinking so we can deliver the tailored, thoughtful work and problem-solving abilities that our clients expect. We invite you to learn more about us by visiting williamblair.com.

William Blair is an equal opportunity employer. It complies with all laws and regulations that prohibit discrimination in employment practice because of race, color, religion, creed, ancestry, marital status, gender, age, national origin, sexual orientation, unfavorable discharge from the military service or on the basis of a physical or mental disability that is unrelated to the employee's ability to perform the duties of the job applied for. EOE m/f/d/v

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