Data​/AI Engineer

Specialty Networks is an integrated, multi-specialty organization with GPOs, Life Sciences, and Research solutions in Urology, Gastroenterology, and Rheumatology. Specialty Networks solutions include population health management, patient engagement, clinical research, and workflow automation technologies to achieve Center of Excellence status in Standards of Care, Clinical Research, Practice Operations, and Value-based Care. Specialty Networks leverages the Power of its Network, represented by over 10,000 providers, to help independent physician practices, industry, wholesalers/distributors, payers, and policymakers improve patient outcomes.

Specialty Networks’ PPS Analytics platform analyzes data from electronic medical records (EMR), practice management, imaging, and dispensing systems and transforms it into meaningful and actionable insights for providers and other stakeholders by using artificial intelligence and modern data analytics capabilities.

Location:

This role is remote and can be based anywhere within the United States. Candidates must be able to work within EST business hours (9a-5p EST).

The Senior Data/AI Engineer is a senior individual contributor on the Data & AI Engineering team responsible for leading the design and delivery of data and AI solutions across our Lakehouse and SQL Server environments. The responsibility of the role is to own projects from problem framing through scoping, architecture, prototyping, and production deployment.

Work spans modern healthcare data platforms and AI engineering, including medallion architecture (bronze/silver/gold), Delta Lake, T‑SQL ETL, and natural language AI capabilities such as NLP/NLU, retrieval‑augmented generation (RAG), document‑level LLM extraction, and agentic frameworks applied to EHR/EMR, practice management (PM), pharmacy, claims, and clinical note data.

• Support the design and delivery of data and AI solutions across Lakehouse and SQL Server environments.
• Own projects end‑to‑end, from problem framing and scoping through architecture, prototyping, and production deployment.
• Develop and implement modern healthcare data platforms and AI engineering solutions, including medallion architecture (bronze/silver/gold), Delta Lake, and T‑SQL ETL.
• Design and build natural language AI capabilities such as NLP/NLU, retrieval‑augmented generation (RAG), document‑level LLM extraction, and agentic frameworks.
• Apply AI and data engineering solutions to diverse healthcare data, including EHR/EMR, practice management (PM), pharmacy, claims, and clinical notes.
• Drive 0‑to‑1 initiatives from concept to production, defining problems, exploring solution spaces, and delivering measurable value.
• Research and prototype novel approaches to complex problems, operating effectively in ambiguous environments.
• Serve as a technical lead on cross‑functional initiatives, establishing project‑level technical direction.
• Drive engineering and code quality standards within the team.
• Mentor mid‑level engineers, fostering their growth and development.
• Partner with product, clinical, analytics, and platform teams to translate ambiguous requirements into robust, production‑ready systems.
• Operate fluently across Databricks and major cloud platforms (Azure, GCP).
• Leverage modern AI‑assisted development tooling (e.g., Claude Code, Codex) to accelerate delivery.

• Experience:
  
  4+ years in Data Engineering, Software Engineering, or Analytics, with a proven track record of taking 0‑to‑1 initiatives from concept to production.
• Education:
  
  Bachelor's degree in Computer Science, Machine Learning, Analytics, Engineering, or a related field highly preferred;
  Master's degree a plus.
• Data Platform Expertise: 3+ years of hands‑on experience with Databricks and/or Snowflake, a major cloud platform (Azure, GCP, or AWS), PySpark, Spark SQL, and Delta Lake fundamentals (ACID, MERGE, OPTIMIZE/ZORDER, schema evolution).
• SQL Proficiency:
  Experience with T‑SQL on Microsoft SQL Server (or PLSQL/Oracle), including stored procedures, views, and functions, and navigating large codebases.
• AI/ML/NLP Production
  
  Experience:
  
  Proven experience (with healthcare data context)…