Yes — here is the full LinkedIn-optimized JD. I’ve kept the AI/ML, cloud, MLOps, healthcare, security, and data-engineering requirements intact, removed the source attribution, and did not add unsupported requirements.
About the Role
Vida Health is seeking a Principal AI/ML Engineering Lead to help build and scale the technology platform supporting its personalized healthcare products. Vida is rebuilding its data platform with a strong focus on protecting patient data, governing data sharing, enabling self-service analytics, and creating a foundation for AI/ML capabilities.
This is a hands-on engineering leadership role spanning AI/ML, software engineering, data engineering, cloud infrastructure, DevOps, security, and production reliability. The Principal AI/ML Engineering Lead will help establish the technical patterns and infrastructure needed to safely deploy machine learning and AI capabilities, including model serving, inference, feature and training pipelines, model lifecycle management, and LLM applications.
The role is suited to a generalist engineer who can work deeply in one technical area while moving effectively across backend, infrastructure, data, and AI/ML systems.
Key Responsibilities
Contribute across the data and platform architecture, including:
Data ingestion
Data transformation
Canonical data models
Entity resolution
Event backbones
Configuration as code
API and serving layers
Strengthen DevOps and platform reliability through:
CI/CD
Infrastructure as code
Environment management
Production observability
Metrics, logs, and traces
Service-level objectives
Partner with Security and IT teams on:
Data classification
Access-control enforcement
Secrets and key management
Security controls aligned with HIPAA and HITRUST
Build the foundation for Vida's AI/ML platform, including:
Model serving
Inference gateways
Feature pipelines
Training-data pipelines
Model registries
Model evaluation
Model deployment
Model monitoring
Integrate AI and machine learning models into production applications.
Support LLM applications with appropriate grounding and guardrails.
Maintain controlled boundaries for protected health information and ensure AI/ML implementations do not create pathways for sensitive data leakage.
Favor in-VPC or local inference where required to protect sensitive data.
Work with existing technical leads to increase AI/ML fluency across platform, security, and DevOps teams.
Establish technical patterns and practices that other engineering teams can build upon.
Contribute to additional platform, AI/ML, data, security, and engineering initiatives as needed.
Work effectively in an environment with ambiguity while maintaining a strong focus on shipping production-ready solutions.
Required Qualifications
Bachelor’s degree or higher.
7–10+ years of experience building and scaling production-grade machine learning or AI systems.
Demonstrated experience as a generalist Software Engineer working across backend, infrastructure, and data.
Substantial hands-on experience building and deploying AI/ML systems in production.
Experience with:
MLOps
Model serving
Inference infrastructure
Feature pipelines
Data pipelines
Production AI/ML applications
Strong cloud engineering experience, ideally with Google Cloud Platform (GCP).
Experience with Google Cloud technologies such as:
Vertex AI
BigQuery
Cloud Run
Pub/Sub
Cloud SQL
Google Kubernetes Engine (GKE)
AWS or Azure cloud equivalents are also welcome.
DevOps and production reliability experience with:
CI/CD
Terraform or similar infrastructure-as-code tools
Containers
Kubernetes
Production observability
Strong data engineering skills, including:
SQL
Data pipelines
dbt
Data warehousing
Security-focused mindset and ability to work with sensitive data in a regulated environment.
Experience with LLM applications, including:
Retrieval
Evaluation
Guardrails
Knowledge graphs
Ability to work comfortably with ambiguity and move between different areas of the technology stack.
Ability to work hands-on while collaborating with platform, security, DevOps, and engineering teams.
Preferred Qualifications
Experience with entity resolution.
Experience with Master Data Management (MDM).
Experience working in healthcare or another regulated data environment.
Familiarity with HIPAA or HITRUST.
Experience with GraphQL.
Experience with a federated serving layer.
Experience with privacy-enhancing technologies.
AI/ML & MLOps Environment
Artificial Intelligence
Machine Learning
MLOps
Model Serving
Model Inference
Inference Gateways
Feature Engineering and Feature Pipelines
Training Data Pipelines
Model Lifecycle Management
Model Registry
Model Evaluation
Model Deployment
Model Monitoring
Large Language Models (LLMs)
LLM Retrieval
LLM Grounding
AI Guardrails
Knowledge Graphs
Cloud, Data & Infrastructure
Google Cloud Platform (GCP)
Vertex AI
BigQuery
Cloud Run
Pub/Sub
Cloud SQL
Google Kubernetes Engine (GKE)
AWS
Azure
Kubernetes
Containers
Terraform
CI/CD
Infrastructure as Code
Observability
Metrics
Logs
Traces
Service-Level Objectives
SQL
dbt
Data Warehousing
Data Ingestion
Data Transformation
Canonical Data Models
Entity Resolution
APIs
Event-Driven Architecture
Security & Compliance The role requires a strong security mindset because the platform handles sensitive healthcare information. Responsibilities include protecting protected health information, enforcing data classification and access controls, managing secrets and keys, and implementing controls aligned with healthcare security and compliance requirements.
Relevant areas include
Protected Health Information (PHI)
HIPAA
HITRUST
Data Classification
Access Control
Secrets Management
Key Management
Privacy-Enhancing Technologies
Secure AI/ML Infrastructure
Controlled Inference Environments
Work Environment
Position: Principal AI/ML Engineering Lead
Location: Madison, WI, US
Work Arrangement: Remote
Employment: U.S.-based
Posted: September 26, 2026
Salary: $250,000–$275,000 per year
Work Authorization: Applicants must be authorized to work in the U.S.
Visa Sponsorship: Vida is unable to sponsor work visas.
International Work: International work is prohibited; employees must reside in or be able to work from the U.S.
Vida is authorized to do business in many, but not all, U.S. states. Eligibility depends on the state where the employee is located and able to work.
About Vida Health
Vida Health is a virtual, personalized obesity care provider using evidence-based treatment to help patients manage obesity and related conditions, including diabetes, high blood pressure, anxiety, and depression.
Vida combines technology with healthcare providers including Obesity Medicine-Certified Physicians, Registered Dietitians, Expert Coaches, and Licensed Therapists to provide whole-person care. The company works with Fortune 100 companies, national payers, and large healthcare providers.
The technology organization is rebuilding its data platform to support secure data use, self-service analytics, and future AI/ML capabilities while maintaining strong protections around patient information.
Equal Employment Opportunity
Vida is an Equal Employment Opportunity and Affirmative Action employer. Qualified applicants receive consideration without regard to legally protected characteristics. Vida also considers qualified applicants with criminal histories consistent with applicable federal, state, and local law.
Vida is committed to recruiting, developing, and retaining talent from diverse candidate pools and provides reasonable accommodations for qualified individuals with disabilities and disabled veterans during the application process.