## About the Role
Vida Health is seeking a Principal AI/ML Engineering Lead to help build and scale the data and AI/ML platform powering its healthcare technology.
Vida is rebuilding its data platform with a strong focus on patient data protection, data governance, secure data sharing, self-serve analytics, and production AI/ML capabilities. In this role, you will take a hands-on engineering approach across AI/ML, software, data, infrastructure, DevOps, and security while establishing scalable patterns for future platform development.
You will work closely with platform, security, IT, and DevOps teams to build production-grade systems that enable AI/ML capabilities while maintaining strong controls around protected health information (PHI) and regulated healthcare data.
## Key Responsibilities
### Data & Platform Engineering
Contribute across the platform, including:
Data ingestion
Data transformation
Canonical data models
Entity resolution
Event backbone
Configuration as code
API and serving layers
Help build scalable and reliable infrastructure for data and AI/ML workloads.
### DevOps & Reliability
Strengthen DevOps and production reliability across the platform.
Build and maintain CI/CD pipelines and infrastructure as code.
Support environment management and deployment workflows.
Implement production observability across metrics, logs, traces, and service-level objectives (SLOs).
Apply containerization and Kubernetes-based infrastructure where appropriate.
### Security & Healthcare Data Protection
Partner with Security and IT teams on platform security and data protection.
Support data classification and access-control enforcement.
Implement secure secrets and key management practices.
Maintain controls aligned with HIPAA and HITRUST requirements.
Ensure protected health information remains within controlled boundaries.
Favor in-VPC or local inference where required to protect sensitive data.
Ensure AI/ML implementations do not introduce paths for healthcare or patient data leakage.
### AI/ML Platform Engineering
Build the foundation for the organization's AI/ML platform.
Develop model serving and inference gateway capabilities.
Build feature and training data pipelines.
Support the complete model lifecycle, including:
Model registry
Model evaluation
Model deployment
Model monitoring
Integrate LLM applications with appropriate grounding and guardrails.
Support retrieval, evaluation, and knowledge-graph-based AI/ML applications.
Integrate machine learning models into production applications.
### Technical Leadership
Work alongside existing team leads to increase AI/ML fluency across platform, security, and DevOps teams.
Establish engineering patterns and technical approaches that other teams can build upon.
Work effectively across the technology stack while maintaining hands-on ownership.
Take on additional responsibilities as needed.
## Required Qualifications
Bachelor's degree or higher.
7–10+ years of experience building and scaling production-grade AI/ML or machine learning systems.
Demonstrated experience as a generalist Software Engineer working across backend engineering, infrastructure, and data.
Significant hands-on experience building and deploying AI/ML systems in production.
Experience with:
MLOps
Model serving and inference infrastructure
Feature pipelines
Data pipelines
Production model integration
Strong cloud engineering experience, ideally with Google Cloud Platform (GCP).
Experience with GCP services such as:
Vertex AI
BigQuery
Cloud Run
Pub/Sub
Cloud SQL
GKE
AWS or Azure cloud experience is also welcome.
Strong DevOps and reliability engineering skills.
Experience with:
CI/CD
Terraform or similar infrastructure-as-code tools
Containers
Kubernetes
Production observability
Strong data engineering capabilities, including:
SQL
Data pipeline tooling such as dbt
Data warehousing
Security-focused mindset and ability to work with sensitive data in regulated environments.
Experience with LLM applications, including retrieval, evaluation, guardrails, and knowledge graphs.
Comfortable working in ambiguous environments with a strong bias toward shipping production solutions.
Ability to work deeply within a specific technical area while moving effectively across the broader technology stack.
## Preferred Qualifications
Experience with entity resolution or master data management (MDM).
Experience working in healthcare or another regulated data environment.
Experience with GraphQL or federated serving layers.
Experience with privacy-enhancing technologies.
Familiarity with HIPAA or HITRUST.
## Core Technical Skills
AI/ML Engineering
Machine Learning Systems
MLOps
Model Serving
Inference Infrastructure
LLM Applications
Retrieval-Augmented Applications
AI Guardrails
Knowledge Graphs
Feature Engineering & Pipelines
Data Engineering
SQL dbt
Data Warehousing
Python/Software Engineering
Backend Engineering
GCP / Google Cloud
Vertex AI
BigQuery
Cloud Run
Pub/Sub
Cloud SQL
GKE
AWS / Azure
Terraform
Kubernetes
Docker / Containers
CI/CD
Observability
Infrastructure as Code
Data Security
HIPAA
HITRUST
Entity Resolution
Master Data Management
GraphQL
## Work Arrangement
100% Remote
Location listed: Garland, TX, US
## Compensation
$250,000–$275,000 per year
## About Vida Health
Vida Health provides virtual, personalized healthcare focused on helping people improve their health and manage conditions including obesity, diabetes, high blood pressure, anxiety, and depression.
Vida combines technology with healthcare professionals, including Obesity Medicine-Certified Physicians, Registered Dietitians, Expert Coaches, and Licensed Therapists, to provide whole-person care.
## Equal Employment Opportunity
Vida is an Equal Employment Opportunity and Affirmative Action employer. Diversity is a core part of Vida's approach and workplace culture.
## Apply Now
If you are a senior AI/ML Engineering leader and hands-on Software Engineer with experience building production AI/ML systems, cloud infrastructure, data platforms, MLOps, and secure applications in regulated environments, apply now for the Principal AI/ML Engineering Lead opportunity.