Lead Engineer, Analytics Platform & AI

Hsmconsulting; Chicago (IL); On-site; USD 140,000 - 180,000; Full time

Job summary

Huron is seeking a Full Stack Lead Engineer for Market Insights to guide end-to-end analytics platform development, from data layer to UI, and embed AI capabilities. You will write and review code, set architecture, and lead engineers while collaborating with product management, data engineering, and data science to accelerate AI-enabled insights delivery.

This hands-on leadership role requires mentoring, establishing engineering practices, and clear communication of decisions to stakeholders.

Qualifications

• 8+ years of professional software engineering experience, including full stack development across front end and back end technologies.
• 3+ years leading or mentoring engineers.
• Experience applying AI or machine learning within production analytics or data products.
• Strong frontend skills with TypeScript, JavaScript, and React.
• Strong backend skills in Python and SQL.
• Solid understanding of relational databases and SQL.
• Working knowledge of AWS services (Lambda, S3, Redshift, Glue, Athena).
• Experience with infrastructure as code (CloudFormation, AWS CDK).
• Version control with Git.
• Experience delivering software using Agile methodologies.

Responsibilities

• Full stack product development across frontend and backend.
• Lead design and development across the stack, APIs and data layer.
• Set technical direction for scalable, secure, high-performance analytics solutions on AWS.
• Collaborate with product management on roadmap and feature delivery using Agile practices.

Skills

TypeScript

Tools

React

JavaScript

Python

SQL

AWS

Git

CloudFormation

AWS CDK

Job description

Huron helps its clients drive growth, enhance performance and sustain leadership in the markets they serve. We help healthcare organizations build innovation capabilities and accelerate key growth initiatives, enabling organizations to own the future, instead of being disrupted by it. Together, we empower clients to create sustainable growth, optimize internal processes and deliver better consumer outcomes.

Health systems, hospitals and medical clinics are under immense pressure to improve clinical outcomes and reduce the cost of providing patient care. Investing in new partnerships, clinical services and technology is not enough to create meaningful and substantive change. To succeed long-term, healthcare organizations must empower leaders, clinicians, employees, affiliates and communities to build cultures that foster innovation to achieve the best outcomes for patients.

Joining the Huron team means you'll help our clients evolve and adapt to the rapidly changing healthcare environment and optimize existing business operations, improve clinical outcomes, create a more consumer-centric healthcare experience, and drive physician, patient and employee engagement across the enterprise.

Join our team as the expert you are now and create your future.

Market Insights is Huron's analytics product suite, built on a foundation of tens of billions of medical claims, millions of clinical providers, and hundreds of millions of unique patient lives. We are looking for a Full Stack Lead Engineer to guide the technical direction of this platform end to end, from the data layer through the user interface, with a mandate to embed AI directly into how our analytics products are built and how they deliver insight to clients.

This is a hands on leadership role. You will write and review code, set architecture and technical standards, and lead a team of engineers, while partnering closely with product management, data engineering, and data science to bring intelligent, AI enabled analytics capabilities to market faster.

Responsibilities

• Full stack product development
• Lead design and development across the stack: responsive front end interfaces, APIs and services, and the underlying data layer for analytics products.
• Set technical direction and architecture for scalability, security, and performance of AWS based analytics solutions.
• Collaborate with product management on roadmap, prioritization, and feature delivery using Agile practices.

AI and machine learning in analytic s

• Identify and lead opportunities to embed AI and Agentic AI capabilities into analytics products: predictive models, natural language interfaces over data, automated insight generation, and generative AI features that help clients act faster on their data.
• Partner with data scientists to move machine learning models from prototype into reliable, production grade services.
• Evaluate and apply large language model based tools where they add measurable client value, with attention to data privacy, accuracy, and healthcare compliance requirements.

Data engineering

• Design and maintain ETL and data pipeline processes that feed dashboards, models, and client facing reporting.
• Work with cloud data services, including S3, Redshift, Glue, Lambda, and Athena, to build scalable data infrastructure.
• Uphold data governance, quality, and healthcare data handling standards across the platform.

Team leadership

• Support, and mentor a team of engineers, providing technical guidance and career development.
• Establish and continuously improve engineering practices, code quality standards, and delivery processes.
• Communicate progress, risks, and technical decisions clearly to product leadership and cross functional stakeholders.

Qualifications

Required:

• 8 or more years of professional software engineering experience, including full stack development across both front end and back end technologies.
• 3 or more years leading or mentoring engineers, formally or informally.
• Demonstrated experience applying AI or machine learning within a production analytics or data product, such as predictive modeling, recommendation systems, or generative AI features.
• Strong front end development skills in TypeScript, JavaScript, and React.
• Strong back end skills in Python, and an equivalent language used for analytics and API development.
• Solid understanding of relational databases and SQL.
• Working knowledge of core AWS services relevant to data and analytics, including Lambda, IAM, S3, Redshift, Glue, and Athena.
• Experience with infrastructure as code using AWS CloudFormation and the AWS CDK.
• Experience with version control systems, particularly Git.
• Experience delivering software using Agile methodologies.
• Excellent written and verbal communication skills, with the ability to explain technical tradeoffs to non-technical stakeholders.

Preferred:

• Familiarity with healthcare data interoperability standards, such as ANSI X12, HL7, and FHIR.
• Experience with healthcare claims data is a plus.