Weave
healthcare communication
PrincipalEngineer-GenAIApplications&MLOps
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“Principal Engineer - GenAI Applications & MLOps at Weave. Skills: GenAI Applications, MLOps, Machine Learning, AI, distributed systems architecture, cloud-native infrastructure. Design and develop ML infrastructure, tooling, and models to help teams deliver world class experiences. Build internal and external products and platforms to enable teams to incorporate AI into their features and customer facing products”
What You'll Achieve.
scalability of our ML infrastructure; ability of our product teams to deliver world-class, AI-driven experiences to 30, 000+ healthcare practices; delivered measurable business outcomes
Industry & Context.
problem-solve; Cross-Team Problem Solving; consult with teams on common ML patterns/tradeoffs
What They're Looking For.
Must Have
12+ years of software engineering experience with progressive technical leadership scope, Demonstrable experience building and deploying ML driven B2B multi-tenant applications in production environments at scale for external products and customers, Deep expertise in distributed systems architecture, including building and operating services that handle hundreds of millions of transactions and terabytes of data, 8+ years of experience in Machine Learning or AI, preferably with a focus on natural language, Expertise with modern ML tools and techniques such as LLMs, RAG, Prompt Engineering, Fine Tuning, LLM evaluations, multi-modal models, and others, background in scalable data stores—both relational (PostgreSQL at scale, Vitess, Spanner) and NoSQL (Bigtable, Redis, etc. ), Operational experience with cloud-native infrastructure on GCP or AWS, including Kubernetes, infrastructure-as-code, and highly available system design, Track record of leading cross-team technical initiatives that delivered measurable business outcomes, Demonstrated ability to influence without direct authority, build consensus across organizational boundaries, and translate technical tradeoffs into business terms
Nice to Have
Expertise with customer facing GenAI at scale, in production, Expertise building low latency high accuracy AI Agents, Background in compliance-heavy environments (healthcare, fintech) with experience navigating regulatory requirements in technical design, History of external technical leadership: open source contributions, conference speaking, or published technical writing
What You'll Do.
Design and develop ML infrastructure
and models to help teams deliver world class experiences
Build internal and external products and platforms to enable teams to incorporate AI into their features and customer facing products
Translate product goals into actionable engineering plans and build scalable
resilient services for data integration and event processing
Help product and development teams understand the data lifecycle and consult with teams on common ML patterns/tradeoffs
Coach and collaborate inside and outside the team to elevate technical standards
and testable code while working in a cloud environment
Monitor the industry landscape
anticipate where technological advances are heading
and ensure Weave stays ahead of the curve
Cut through noise and hype to identify genuine strategic advocate for and lead key initiatives that prepare Weave for emerging challenges
Shape company-wide standards for engineering excellence
and reliability in distributed systems
Actively mentor Staff and Senior Engineers across the fellowship
developing the next generation of technical leaders
Elevate architectural thinking across teams through design reviews
documentation standards
and hands-on guidance
Build organizational capability that persists beyond your individual contributions
How You'll Work.
Team & Collaboration
partnering with Engineering Managers, Staff Engineers, and cross-functional stakeholders to drive architectural coherence and strategic technical initiatives; Coach and collaborate inside and outside the team to elevate technical standards; Actively mentor Staff and Senior Engineers across the fellowship; Elevate architectural thinking across teams through design reviews, documentation standards, and hands-on guidance; build consensus across organizational boundaries
Communication Scope
translate technical tradeoffs into business terms
Process & Methodology
Translate product goals into actionable engineering plans
Full Job Description
Weave is looking for a Principal Engineer to join the Machine Learning Team, where you will be at the forefront of enabling product innovation and building AI-powered applications. In this role, you will help design how teams across Weave build out AI-powered features, serving as a technical leader who bridges the gap between sophisticated machine learning and practical, customer-facing products. As a technical cornerstone, you will design the platforms that allow our engineering organization to incorporate AI into their features seamlessly. Your success is measured by the scalability of our ML infrastructure and the ability of our product teams to deliver world-class, AI-driven experiences to 30,000+ healthcare practices. This is a strategic leadership position requiring deep expertise in MLOps and GenAI. You will consult with teams on common ML patterns and tradeoffs, ensuring that our technical strategy for data and intelligence positions Weave as a leader in the healthcare communication space. TEAM INFO The Messaging Fellowship encompasses multiple engineering teams responsible for Weave's core communication capabilities—appointment reminders, review requests, missed-call texts, two-way messaging, and the infrastructure that delivers billions of messages reliably at scale. You will work across these teams as a technical leader, partnering with Engineering Managers, Staff Engineers, and cross-functional stakeholders to drive architectural coherence and strategic technical initiatives. This position is remote (US-based) Reports to: Sr Director of Engineering WHAT YOU WILL OWN INFRASTRUCTURE & DELIVERY - Design and develop ML infrastructure, tooling, and models to help teams deliver world class experiences - Build internal and external products and platforms to enable teams to incorporate AI into their features and customer facing products - Translate product goals into actionable engineering plans and build scalable, resilient services for data integration and eve
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