Solution Advancement Engineer, Analytics Products

Huron Consulting Group · Chicago · $110,000–$150,000 (stated in the posting)

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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.

In this role, you will: 

• • Own end-to-end delivery of Huron's Insights applications (e.g., Periop Insights, IP Insights) across active client engagements — from data pipeline and app configuration through client QC, UAT, and sign-off. 
  • Contribute core engineering to the Insights Agent (IAA) platform — LLM agent loop design, subagent architecture, and structured output/evaluation patterns. 
  • Build and deploy interactive applications using R (Shiny) and Python, deployed via Posit Connect and the team's Docker-based mono repo. 
  • Collaborate directly with healthcare clients and clinical consultants, translating domain requirements (benefit models, OA report structures, clinical workflows) into software. 
  • Influence platform architecture decisions — this role shapes how the product evolves, not just executes against a spec. 
  • Mentor other engineers and help drive engineering best practices across a small, high-autonomy team. 

Key Responsibilities 

• • Lead deployment and configuration of Insights applications across multiple concurrent client engagements, managing data translation pipelines, app config, QC, and comparison testing against legacy (e.g., Power BI) reporting. 
  • Design and build LLM agent capabilities on the IAA platform — subagent patterns, registry/dispatch architecture, and evaluation frameworks (pydantic-evals). 
  • Maintain and extend Docker-based mono repo deployment infrastructure, including version tagging, rollback procedures, and CI/CD (Jenkins). 
  • Work with AWS data lake infrastructure (Athena, S3, RDS) to support client data pipelines. 
  • Translate UAT feedback and clinical stakeholder input into architectural and UX decisions — this is a product-ownership role, not a pure feature-delivery role. 
  • Drive quality, performance, and delivery speed across multiple simultaneous client engagements in a consulting-adjacent environment where requirements evolve. 

Required Qualifications 

• • U.S. work authorization is required. 
  • Bachelor's degree in Computer Science, Data Science, Engineering, or related field (or equivalent experience). 
  • 6+ years of software development experience, including full-stack ownership of a production product. 
  • Strong proficiency in Python (required); working proficiency in R for Shiny-based analytics apps. 
  • Experience with LLM/agent-based application development — Pydantic AI, RAG, structured outputs, or comparable agent orchestration frameworks. 
  • Experience with Docker and containerized deployment — comfort with rollback procedures and deployment scripting, not just application code. 
  • Proven experience owning a client-facing analytics or software product end-to-end — data layer through UI through client sign-off. 
  • Self-starter comfortable with ambiguity, multi-client context-switching, and fast iteration based on live client feedback. 
  • Excellent collaboration and customer-facing communication skills — this role runs UAT sessions and works directly with clinical stakeholders. 

Preferred Qualifications 

• • Healthcare analytics domain experience (Periop, inpatient, ED metrics, OR utilization) — not required, but significantly accelerates onboarding. 
  • Experience with Posit Connect or similar platforms for deploying R/Shiny analytics products. 
  • Experience with AWS data lake architecture (Athena, S3) or other cloud-based data platforms. 
  • Experience with Snowflake or other modern cloud data warehouse platforms — the team is moving to Snowflake as its warehouse platform in 2027. 
  • Agile/Scrum development process familiarity. 
  • Experience in a consulting or professional-services environment where deliverables are client-visible and timelines tie to engagement milestones.
    

The estimated base salary for this job is $110,000 - $150,000 USD. The range represents a good faith estimate of the range that Huron reasonably expects to pay for this job at the time of the job posting. The actual salary paid to an individual will vary based on multiple factors, including but not limited to specific skills or certifications, years of experience, market changes, and required travel. This job is also eligible to participate in Huron’s annual incentive compensation program, which reflects Huron’s pay for performance philosophy. Inclusive of annual incentive compensation opportunity, the total estimated compensation range for this job is $126,500 - $172,500 USD. The job is also eligible to participate in Huron’s benefit plans which include medical, dental and vision coverage and other wellness programs. The salary range information provided is in accordance with applicable state and local laws regarding salary transparency that are currently in effect and may be implemented in the future.

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