AI Engineer

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🔥 5 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

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Vytalize Health

WebsiteLinkedInAll Job Openings

201 - 500 employees

🤝 B2B

☁️ SaaS

⚕️ Healthcare Insurance

💰 $100M Series C - Vytalize Health on 2023-02

B2B • SaaS • Healthcare Insurance

Vytalize Health is a healthcare technology and services company that helps primary care practices and Accountable Care Organizations (ACOs) transition to value-based care. It combines data-driven analytics, virtual and in-home clinical support, and care management services to improve patient outcomes, enable Medicare-approved remote services for chronic conditions, and help practices earn shared savings under value-based contracts. Vytalize partners with independent PCPs, group practices, community health centers and existing ACOs to deliver clinical enablement, practice-tailored workflows, and performance insights.

📋 Description

• Design, build, and maintain agentic systems and LLM-powered applications that automate healthcare workflows, data pipelines, and clinical decision support — from conception through production deployment • Build and orchestrate agents using LLM APIs (OpenAI, Anthropic, etc.) and agentic frameworks (LangChain, LangGraph, CrewAI, or custom orchestration) to solve complex, multi-step healthcare problems • Develop prompt libraries, agent instructions, and reusable "skills" that improve agent accuracy, consistency, and reliability across different use cases and data domains • Build validation and confidence-scoring layers that flag low-confidence agent decisions for human review before production deployment; establish guardrails and review workflows for agent-authored code and outputs • Own end-to-end delivery of AI-automated systems — from problem scoping and requirements gathering through agent development, testing, and validated production deployment • Implement rigorous evaluation and QA frameworks for agentic systems — including golden datasets, test cases, output validation, hallucination detection, and regression testing • Establish and maintain evaluation metrics for agent performance, reliability, and clinical appropriateness; measure agent accuracy, hallucination rates, clinical validity, and real-world impact • Implement observability, evaluation, and regression testing frameworks specific to agentic systems — decision tracing, lineage logging, and performance tracking • Collaborate with data engineering and platform teams to integrate agent-built outputs (dbt models, transformation logic, recommendations) into existing data architectures and clinical workflows • Ensure all agentic systems comply with healthcare regulations (HIPAA, FDA guidance on AI/ML) and responsible AI practices — including explainability, auditability, and clinician trust • Continuously evaluate new LLM models, agent frameworks, prompt engineering techniques, and tooling; recommend adoption or migration based on healthcare-specific requirements (accuracy, cost, latency, regulatory alignment) • Partner with data engineering to establish robust data validation and input validation layers for agents — agents are only as good as the data they operate on • Lead experimentation and measurement of AI-automated systems impact on speed, quality, compliance, and cost across healthcare workflows • Document agent architectures, prompt strategies, evaluation frameworks, and best practices for both technical and non-technical stakeholders • Mentor AI Connector Engineers and other team members on agentic development patterns, LLM-powered application design, and responsible AI practices • Work on-call as needed to support production agentic systems, troubleshoot agent issues, and respond to performance degradation or hallucination detection

🎯 Requirements

• 3+ years of professional experience in data engineering, backend engineering, machine learning, or a related field • 1+ years of hands-on experience building with LLM APIs and agentic orchestration frameworks — not just using AI coding assistants, but architecting agentic systems • Strong Python and SQL proficiency • Experience with cloud data platforms (AWS, Databricks) • Solid understanding of data modeling, ETL/ELT patterns, and medallion architecture (Bronze/Silver/Gold) • Experience building and consuming APIs • Demonstrated experience with prompt engineering, agent evaluation, and validating LLM outputs • Experience designing evaluation frameworks, test cases, and quality assurance for AI/ML systems • Demonstrated ability to measure and track AI system performance through metrics and KPIs (accuracy, precision, recall, hallucination rates) • Strong debugging and analytical skills, especially in ambiguous or novel technical territory • Excellent written and verbal communication skills — this role requires documenting agent reasoning, decisions, and limitations clearly for both technical and non-technical audiences • Comfortable working in a fast-moving environment with incomplete information and rapidly evolving AI/ML capabilities.

🏖️ Benefits

• Competitive salary • Flexible working hours • Professional development budget • Home office setup allowance • Global team events