About Vi
Vi is an enterprise AI platform for health enterprises – healthcare, biopharma, and wellness. We deploy agentic AI and predictive models into production environments where the output drives next best actions for patients, care teams, and operations to deliver ROI and improve health outcomes.
We are looking for an AI Full Stack Engineer to be the technical owner of Pulse, Vi's client-facing analytics product: an LLM-driven system that lets health enterprises query their data in natural language and get back answers, visualizations, and recommended actions.
You will carry full accountability and single ownership for the architecture, development, and delivery. Tackling roadmap, features development, and system stability.
What you'll do
Architecture - own the system architecture, determine the technical approach to building the system, and main capabilities within it.
Delivery - own delivery of Pulse as a live and production system to clients.
Non-functional integrity - Reliability, performance, security, observability, and quality across your scope, in a HIPAA-regulated environment handling real patient data.
An AI-native operating model - Agentic development tooling, automated evaluation, and adapt as models and tooling keep changing.
Requirements
4+ years as a Full Stack Engineer, building and maintaining production systems.
AI Engineering capabilities, Production-grade experience with LLM application patterns: agents, orchestration frameworks, RAG.
Build with agentic coding tools daily, and own the output.
Strong backend and data foundations, APIs, real-time and event-driven services, and high-scale distributed data pipelines in Python with Spark or comparable frameworks.
Cloud Capabilities (AWS), you’ve deployed applications to production, used by real customers. Storage, compute (Serverless & k8s), data pipelines (Airflow/Glue/EMR), CDN, security & networking, CI/CD pipelines (GitHub Actions). Worked closely with Infrastructure/DevOps teams.
Exceptional learning velocity, you absorb new domains, tools, and model capabilities faster than the market moves. Being able to tell the difference between what makes true impact and AI slop.
Fluent English, working directly with US-based stakeholders, technical and commercial.