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Principal Engineer - GenAI Applications & MLOps

Job in Washington, District of Columbia, 20001, USA
Listing for: Weave
Full Time position
Listed on 2026-07-05
Job specializations:
  • Software Development
    Cloud Engineer - Software, Software Architect, AI Engineer (Applied/Software)
Job Description & How to Apply Below

Principal Engineer

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.

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  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 event processing

Cross-Team Problem Solving

  • 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
  • Write high-quality, performant, sustainable, and testable code while working in a cloud environment

Strategic Technical Leadership

  • 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 value; advocate for and lead key initiatives that prepare Weave for emerging challenges
  • Shape company-wide standards for engineering excellence, observability, and reliability in distributed systems

Mentorship & Organizational Capability

  • 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
What You Will Need to Accomplish the Job
  • 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
  • Strong background in scalable data stores—both relational (PostgreSQL at scale, Vitess, Spanner) and No

    SQL (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…
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