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

Join William Blair, the Premier Global Partnership.

We’re seeking a Data & AI Engineer to design, build, and maintain intelligent, scalable data and AI‑enabled platforms supporting our Equities business across Trading, Research, and Sales. This role spans the full software development lifecycle and is responsible for moving data and AI solutions from concept through production, while ensuring reliability, security, and compliance with firm standards.

The ideal candidate brings strong data engineering fundamentals combined with hands‑on experience integrating AI and LLM‑based capabilities into production systems in a regulated environment.

The role will be based in Chicago with a hybrid work schedule.

Key Responsibilities

Data Engineering & Platform Foundations

Design, build, and maintain scalable data pipelines using Databricks, Azure Data Factory, and Azure Synapse
Implement robust ETL/ELT workflows for structured and unstructured financial data across on‑prem and cloud platforms
Ensure data quality, lineage, governance, security, and observability across all pipelines and storage layers
Design and optimize data models and analytical schemas (star/snowflake, partitioning, distribution strategies)
Build reusable ingestion and transformation frameworks to support analytics and AI workloads

AI Integration & Agentic Workflows

Build and deploy AI‑enabled services, agents, and workflows supporting equity research, trading, sales, and client service use cases
Implement LLM‑based and agentic patterns, including Retrieval‑Augmented Generation (RAG), using proprietary firm data
Integrate AI capabilities into existing applications and platforms via APIs, batch jobs, and event‑driven workflows
Partner with Data Science and business stakeholders to translate AI concepts into production‑ready solutions

AI Enablement & Productionization

Productionalize AI and Data Science POCs into secure, scalable, and monitored services suitable for regulated environments
Optimize prompts, embeddings, orchestration logic, and inference workflows for accuracy, performance, cost, and reliability
Ensure AI solutions meet firm standards for security, auditability, explainability, and compliance
Establish operational practices for AI solutions, including monitoring, alerting, lifecycle management, and runbooks

Cloud Modernization & DevOps

Support migration of legacy data and application solutions (SQL, SSIS, Synapse, custom ETLs) to modern Azure‑native architectures
Implement CI/CD pipelines using Azure DevOps and YAML, following infrastructure‑as‑code and automation best practices
Leverage Azure services (Functions, Key Vault, Logic Apps, Automation Runbooks) to build secure, reliable, and maintainable solutions
Develop operational dashboards to monitor pipeline health, SLAs, system performance, and cloud spend

Collaboration & Delivery

Work closely with Product Managers, Software Engineers, Data Scientists, and business stakeholders to define functional and technical requirements
Participate in Agile ceremonies, sprint planning, and retrospectives
Lead testing of new and modified software, analyze issues, and resolve defects efficiently
Document technical designs, integrations, and maintain operational playbooks and runbooks
Monitor industry trends in data engineering, cloud platforms, and AI, and recommend adoption where aligned with firm strategy

Essential Qualifications

Bachelor’s degree in information technology or related field
4–6+ years of hands‑on experience with Databricks, Spark, Azure Data Factory, Azure Synapse, Python, ADLS, and Azure Functions
Strong experience designing and managing Synapse/ADF pipelines, activities, and linked services
Proven ability to build full and incremental data loads from Azure and on‑prem data sources
Experience designing reusable ETL/ELT frameworks and orchestrating pipelines across ADF/Synapse/Databricks
Experience implementing LLM‑enabled or RAG‑based solutions in production environments