Senior Engineer – Semantic & Agentic Intelligence

Cambia Health Solutions•Little Rock, AR

2d•$103,000 - $188,000•Hybrid

About The Position

Cambia is seeking a Senior Engineer for its Data & Analytics Engineering Team, on the Semantic & Agentic Intelligence Squad. The engineer will design, build, and own the semantic foundation and agentic AI capabilities that support governed analytics, intelligent automation, and purpose-built enterprise data products. The role combines dimensional modeling expertise with modern AI and LLM engineering, and serves as a technical lead who mentors engineers, establishes technical standards, and contributes to platform strategy. The position offers a path toward Principal-level engineering, architecture, or people leadership. This is a hybrid role requiring three days per week in an office. Offices are in 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 candidates willing to relocate. The expected salary range depends on location. The national pay structure, applying to Boise and Lewiston, Idaho; Salt Lake City, Utah; Oregon; and Washington, has an expected range of $122,000–$165,000 per year, a full range of $115,000–$188,000, and a 15% bonus target. The regional pay structure, applying to North Dakota and Idaho and Utah locations outside the listed metro areas, has an expected range of $110,000–$149,000 per year, a full range of $103,000–$169,000, and a 15% bonus target. Cambia describes itself as a purpose-driven organization working to create a person-focused and economically sustainable health care system. It offers a hybrid work arrangement, with work-from-home options for most roles subject to wired internet requirements. New hires must have access to a personal mobile device to set up required multi-factor authentication. A background check is required.

Requirements

At least 6 years of relevant experience in Data Engineering, Semantic Modeling, or AI/ML Engineering, including 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 accepted.
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 defining governed metrics in a semantic or metrics layer and building and deploying a semantic layer used directly by business users.
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 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 using 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 AI evaluation frameworks, guardrails, and observability 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 and ICD-10 and CPT/HCPCS.
Strong SQL fundamentals, a consulting-oriented mindset, and hands-on experience building governed, observable AI solutions in complex enterprise environments.

Nice To Haves

Experience supporting a 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 regression and ensemble models such as 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 and regulated environment.
Build LLM and agentic applications, including RAG pipelines, vector search, prompt engineering, and agent orchestration using Snowflake Cortex or comparable tooling.
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, and 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.
Demonstrate technical leadership by breaking down complex work and delivering measurable value in squad and model environments.

Benefits

Competitive base pay and bonus opportunities, with a 15% bonus target for the stated pay structures.
Market-leading 401(k) with a significant company match and potential discretionary contribution based on company performance, with no vesting period.
Medical, dental, and vision coverage for employees and eligible family members, including mental health benefits.
Annual employer contribution to a health savings account.
Generous paid time off that varies by role and tenure, in addition to 10 company-paid holidays.
Up to 12 weeks of paid parental time off, subject to eligibility requirements.
Award-winning wellness programs.
Employee Assistance Fund.
Commute and parking benefits.
Employee resource groups and opportunities to participate in Cambia-supported community outreach programs.
Work-from-home options for most roles, subject to internet requirements.