[Hiring] Lead Engineer, Analytics Platform & AI @Huron

Role Description

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.

We are looking for a Full Stack Lead Engineer to guide the technical direction of our analytics product suite, Market Insights, 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.
• Lead a team of engineers.
• Partner closely with product management, data engineering, and data science.

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 analytics:
  • 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

• 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.
• Hands on experience with large language models, prompt engineering, retrieval augmented generation, or vector databases.
• Experience with MLOps practices for deploying and monitoring machine learning models in production.
• Experience with SQLAlchemy and PostgreSQL.
• Experience with row based databases such as Amazon RDS and Aurora.
• Experience with columnar or data warehouse platforms such as Redshift, Athena, and Snowflake.
• Experience with NoSQL databases such as DynamoDB.
• Experience with a broader range of AWS services beyond the core set, and with Azure DevOps for build and release pipelines.
• Experience with big data technologies such as Spark, or infrastructure as code tools such as Terraform.
• Background in healthcare or higher education analytics.
• AWS certification, such as AWS Certified Solutions Architect or AWS Certified Developer.
• A bachelor's degree in computer science, engineering, or a related field, or equivalent practical experience.

Position Level

Senior Associate

Country

United States of America