Responsibilities:
- Contribute across the platform build: data ingestion, transformation, a canonical data model and entity resolution, an event backbone, configuration as code, and API and serving layers.
- Strengthen DevOps and reliability: CI/CD, infrastructure as code, environment management, and observability across metrics, logs, traces, and service level objectives.
- Partner with Security and IT: data classification and access control enforcement, secrets and key management, and controls aligned with HIPAA and HITRUST.
- Lay the groundwork for the AI/ML platform: model serving and an inference gateway, feature and training data pipelines, model lifecycle (registry, evaluation, deployment, monitoring), and LLM integration with grounding and guardrails.
- Keep protected health information inside controlled boundaries, favor in-VPC or local inference where required, and make sure that adding ML never opens a path for data to leak.
- Work with existing team leads to continue raising the AI and ML fluency of the platform, security, and DevOps teams as you work alongside them, and set the patterns others will build on.
- Additional responsibilities as needed.
Qualifications:
- Bachelor's Degree at a minimum.
- 7-10+ years of experience in building and scaling production-grade machine learning or AI systems.
- Demonstrated experience as a generalist Software Engineer across backend, infrastructure, and data.
- Substantial hands-on experience building and deploying AI/ML systems in production, including MLOps, model serving and inference infrastructure, feature and data pipelines, and integrating models into real applications.
- Strong cloud experience, ideally on Google Cloud (Vertex AI, BigQuery, Cloud Run, Pub/Sub, Cloud SQL, GKE), with AWS or Azure equivalents also welcome.
- DevOps and reliability skills: CI/CD, Terraform or a similar tool, containers and Kubernetes, and production observability.
- Solid data engineering: SQL, pipeline tooling such as dbt, and data warehousing.
- A security mindset and comfort working in a regulated environment with sensitive data. Familiarity with HIPAA or HITRUST is a plus.
- Experience with LLM applications, including retrieval, evaluation, guardrails, and knowledge graphs.
- Comfortable with ambiguity and a bias for shipping. You can go deep in one area and still move fluidly across the stack.
Preferred:
- Experience with entity resolution or master data management.
- Experience in healthcare or another regulated data domain.
- Experience with GraphQL or a federated serving layer.
- Experience with privacy enhancing technologies.
Skills Required
- Bachelor's degree
- 7-10+ years of experience building and scaling production-grade machine learning or AI systems
- Generalist software engineering experience across backend, infrastructure, and data
- Hands-on experience building and deploying production AI/ML systems, including MLOps, model serving, inference infrastructure, feature and data pipelines, and model integration
- Strong cloud experience with Google Cloud, AWS, or Azure
- DevOps and reliability experience with CI/CD, Terraform or similar infrastructure-as-code tools, containers, Kubernetes, and observability
- Data engineering experience with SQL, pipeline tooling such as dbt, and data warehousing
- Security mindset and comfort working with sensitive data in regulated environments
- Experience with LLM applications, including retrieval, evaluation, guardrails, and knowledge graphs
- Experience with entity resolution or master data management
- Experience in healthcare or another regulated data domain
- Experience with GraphQL or a federated serving layer
- Experience with privacy-enhancing technologies
- Familiarity with HIPAA or HITRUST
What We Do
Vida is a virtual care company that combines a human-centric approach with technology to address chronic and co-occurring physical and behavioral health conditions. We provide personalized chronic condition management combined with health coaching and therapy through a mobile and online platform that supports individuals in managing and significantly improving conditions such as diabetes, hypertension, obesity, depression, anxiety, etc. Our platform integrates deeply individual expert care with machine learning and remote monitoring to deliver lasting behavior change, health outcomes and cost savings. Vida is in the business of enabling self-insured employers, health plans and providers to take better care of their employees and members. We are trusted by Fortune 1000 companies, major national payers, and large providers to activate, engage, and empower their employees to live their healthiest lives. Based in San Francisco, CA, Vida is backed by investors including Khosla Ventures, StartX, Aspect Ventures, Canvas, Workday, and Nokia.









