Remote Lead Solutions Engineer - Healthcare Data & AI

AbsoluteCARE Medical Center & Pharmacy

Baltimore (MD)

Remote

USD 120,000 - 170,000

Full time

5 days ago

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Job summary

AbsoluteCARE Medical Center & Pharmacy is seeking a Lead Solutions Engineer to design, build, and support healthcare data pipelines and Agentic AI workflows enabling clinical initiatives, care management, and population health operations.

The role partners with clinical operations, analytics, and technology teams to translate clinical workflow needs into secure, scalable AI-enabled solutions while upholding PHI handling and data governance requirements.

Qualifications

Bachelor’s degree in IT/CS/Data Science or related field, or equivalent work experience.
5+ years of healthcare data experience (provider, value-based care, population health, care management, payer operations, EHR, or related).
5+ years of professional data engineering, analytics engineering, or healthcare data platform experience.
5+ years of hands-on SQL development experience (queries, procedures, data quality).
5+ years of Python experience for data engineering, automation, or AI workflows.
Experience with Microsoft Azure data services (Azure SQL, Data Factory, Data Lake, Functions, Synapse).
Hands-on AI-enabled solutions using Azure OpenAI, GenAI, Agentic AI, RAG, vector DBs, LLM orchestration, governance controls.
Understanding healthcare privacy, PHI handling, data governance, access controls, auditability.

Responsibilities

Design, build, and maintain robust healthcare data pipelines using Python, SQL, and Azure data services.
Design Agentic AI workflows with human-in-the-loop review, traceability, audit logging, and RBAC.
Collaborate with clinical stakeholders to ensure AI workflows support operations without replacing clinical judgment.
Develop reusable data and AI components for clinical summaries, care gap workflows, risk stratification, and care management prioritization.
Develop and optimize ETL/ELT processes integrating payer, clinical, EHR, claims, and operational data.
Support Azure-based data engineering patterns (Azure SQL, Data Factory, Data Lake, Functions).
Implement validation and monitoring controls for AI outputs to reduce risk of incorrect responses.
Maintain HIPAA privacy and data governance in AI/engineering work.