Data & AI Engineer – Equities Technology

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 & Dev Ops Support  migration of legacy data and application solutions (SQL, SSIS, Synapse, custom ETLs) to modern Azure‑native architectures

Implement CI/CD pipelines using Azure Dev Ops 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 field4–6+ 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…