Job Description
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Company Overview
A growing technology organization is developing AI-powered communication products and platforms designed to support more than 30,000 healthcare practices. Its data and AI/ML engineering teams build solutions that enable customer-facing products, including intelligent call and reception capabilities, while providing a shared ML platform that supports engineering teams across the organization.
What You Will Own
Infrastructure & Delivery
- Design and develop ML infrastructure, tooling, and models that enable engineering teams to deliver AI-powered customer experiences.
- Build internal and external products and platforms that allow teams to incorporate AI capabilities into their features and customer-facing products.
- Translate product goals into actionable engineering plans.
- Build scalable and resilient services for data integration and event processing.
- Develop high-quality, performant, sustainable, and testable code within cloud-based environments.
- Drive scalable ML infrastructure and platform capabilities across the organization.
Cross-Team Problem Solving
- Help product and development teams understand the complete data lifecycle.
- Consult with engineering teams on common ML patterns, architectures, and technical tradeoffs.
- Coach and collaborate with teams across the organization to elevate technical standards.
- Partner with Engineering Managers, Staff Engineers, and cross-functional stakeholders to drive architectural coherence.
- Provide technical guidance for integrating AI and ML capabilities into customer-facing applications.
Required Qualifications
- 12+ years of software engineering experience with progressive technical leadership responsibilities.
- Demonstrable experience building and deploying ML-driven B2B, multi-tenant applications in production at scale for external customers.
- Deep expertise in distributed systems architecture, including experience building and operating services handling hundreds of millions of transactions and terabytes of data.
- 15+ years of experience in Machine Learning or AI, with a focus on or significant expertise in audio and voice Generative AI solutions at scale.
- Deep expertise with modern machine learning techniques and tools, including LLMs, RAG, prompt engineering, fine-tuning, and LLM evaluations.
- Strong expertise with high-scale audio and voice models.
- Experience working with scalable relational data stores, including PostgreSQL at scale, Vitess, and Spanner.
- Experience with scalable NoSQL technologies such as Bigtable and Redis.
- Operational experience with cloud-native infrastructure on GCP or AWS.
- Experience with Kubernetes, infrastructure-as-code, and highly available system design.
- Track record of leading cross-team technical initiatives that delivered measurable business outcomes.
- Ability to influence without direct authority and build consensus across organizational boundaries.
- Ability to communicate technical tradeoffs effectively in business terms.
Additional Qualifications
- Expertise delivering customer-facing Generative AI solutions at scale in production environments.
- Experience building low-latency, high-accuracy AI agents.
- Mandatory deep production experience delivering meaningful voice or audio AI solutions for external products and customers.
- Experience working in compliance-heavy environments such as healthcare or financial technology.
- Understanding of regulatory requirements and their impact on technical architecture and system design.
- Demonstrated external technical leadership through open-source contributions, conference presentations, or published technical content.
- Ability to bring strong technical perspectives while remaining open to alternative approaches and ideas.
Reporting
Reports to: Senior Director of Engineering
Work Arrangement: Remote, US-based
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