Senior Engineer – Semantic & Agentic Intelligence

Cambia Health Solutions•Boise, ID

7h•Hybrid

About The Position

Cambia is seeking a Senior Engineer for its Data & Analytics Engineering team, on the Semantic & Agentic Intelligence Squad. The role designs, builds, and owns the semantic foundation and agentic AI capabilities that support governed analytics, intelligent automation, and purpose-built enterprise data products. The engineer serves as a technical lead, applying dimensional modeling and modern AI/LLM engineering expertise, mentoring engineers, driving technical standards, and contributing to platform strategy. The position offers a path toward Principal-level engineering, architecture, or people leadership. The role is hybrid, with three days per week in an office. Locations include Salt Lake City, Boise, Fargo, Portland, Vancouver, Renton, Medford, Burlington, Lewiston, Little Rock, and Springdale. Preference is given to current employees and candidates within commuting distance of Salt Lake City, Boise, Fargo, Lewiston, Little Rock, or Springdale, or those willing to relocate. The hiring range varies by location. Under the national pay structure, the expected range is $122,000–$165,000 per year, with a full range of $115,000–$188,000 and a 15% bonus target. Under the regional pay structure, the expected range is $110,000–$149,000 per year, with a full range of $103,000–$169,000 and a 15% bonus target. Cambia describes its culture as purpose-driven and focused on person-centered, economically sustainable health care. It offers competitive compensation, benefits, career development, community outreach opportunities, and employee resource groups. Most roles have work-from-home options, subject to wired internet requirements. New hires must have access to a personal mobile device for multifactor authentication. A background check is required.

Requirements

At least 6 years of relevant experience in Data Engineering, Semantic Modeling, or AI/ML Engineering, with senior or lead experience.
College degree in Computer Science, Mathematics, Business Administration, or a related field; sufficient years of healthcare industry experience may substitute for a degree.
Equivalent combination of education and experience is considered.
Deep expertise in dimensional modeling, including grain, bridge tables, many-to-many relationships, and slowly changing dimensions.
Strong SQL skills with Snowflake or a comparable cloud data warehouse.
Experience with dbt, ELT/ETL design patterns, and orchestration tools such as Airflow or similar.
Understanding of data governance, security, compliance, and enterprise platform ownership.
Experience defining governed metrics in a semantic or metrics layer and building and deploying a semantic layer used directly by business users.
Experience evaluating AI-generated answers and diagnosing and fixing root causes in the semantic layer.
Experience deploying and monitoring AI agents in a governed, regulated environment.
Experience building LLM or agentic applications involving RAG pipelines, embeddings or vector search, prompt engineering, tool or function calling, and agent orchestration frameworks.
Experience with Snowflake Cortex (Analyst, Search, Agents) or comparable native AI tooling.
Experience implementing evaluation frameworks, guardrails, and observability for AI agents, covering accuracy, hallucination detection, latency, and cost.
Familiarity with scoring techniques such as F1 scoring and related evaluation metrics.
Experience with model or agent monitoring, cost optimization, and performance tuning.
Working knowledge of payer data, including claims (837/835), eligibility, enrollment, and provider data.
Familiarity with healthcare standards including HL7/FHIR, ICD-10, and CPT/HCPCS.
Ability to work in a hybrid arrangement requiring three days per week in an office.
For work-from-home options, a wired, non-satellite, non-cellular internet connection with at least 5 Mb upload and 10 Mb download speeds is required.
Access to a personal mobile device is required to set up multifactor authentication.
A background check is required.

Nice To Haves

Experience with a supported business area, such as Provider Network, Claims, Membership, Digital Solutions, or Pricing.
Experience with ontologies, knowledge graphs, or formal business vocabularies.
Experience building and managing MLOps pipelines and familiarity with machine learning models such as regression and ensemble methods, including KNN, XGBoost, Random Forest, and Decision Trees.
Experience building consumer-facing AI applications or features involving inference.
Experience building multi-tier AI applications or multi-agent workflows, including multimodal LLM experience.
Experience with statistical and predictive modeling, including regression, classification, clustering, and time-series forecasting.
Experience with BI and visualization tools such as Tableau, Power BI, or Looker, and translating analytical findings into business narratives.
Exposure to experimentation and hypothesis testing, including A/B testing and statistical significance.

Responsibilities

Lead and mentor Data and AI Engineers and drive engineering standards and best practices across the squad.
Design, build, and own scalable dimensional models, semantic layers, and governed metric definitions for business users and AI systems.
Develop and deploy AI agents for healthcare use cases, including prior authorization, member support, care gaps, utilization analytics, and anomaly detection, in a governed, regulated environment.
Build LLM and agentic applications, including RAG pipelines, vector search, prompt engineering, and agent orchestration using Snowflake Cortex or comparable tools.
Implement AI Ops practices, including evaluation frameworks, guardrails, observability, and cost and performance optimization for deployed agents.
Optimize platform performance through query tuning, compute sizing, workload isolation, and cost management.
Partner with Analytics, Product, Governance, QA, and Business teams to deliver high-quality, observable, trustworthy data and AI solutions.
Contribute to platform strategy, risk assessments, and adoption of modern practices such as DataOps, CI/CD, and AI tooling.
Ensure data quality, testing, documentation, and knowledge sharing across the team.
Break down complex work and deliver measurable value in squad and model environments.

Benefits

Medical, dental, and vision coverage for employees and eligible family members, including mental health benefits.
Annual employer contribution to a health savings account.
Paid time off that varies by role and tenure.
10 company-paid holidays.
Up to 12 weeks of paid parental time off, subject to eligibility requirements.
401(k) retirement plan with a company match and a potential discretionary contribution based on company performance, with no vesting period.
Bonus opportunities.
Wellness programs that reward participation.
Employee Assistance Fund.
Commute and parking benefits.
Work-from-home options for most roles.
Employee resource groups.
Cambia-supported community outreach opportunities.