Staff Software Engineer, Search

Responsibilities

• Architect and build core backend services, APIs, and data infrastructure that power Zocdoc’s next-generation search platform
• Redesign how provider, availability, and content data is ingested and flows through indexing pipelines into search and ML systems
• Design and optimize low-latency query paths across tier-1 search service, vector search infrastructure, and cross-encoder ranking systems
• Integrate ML model serving, embedding generation, and ranking signals into production backend services through scalable, observable patterns
• Drive architectural direction and set engineering standards across the Search Services organization through design docs, technical deep dives, and high-signal code reviews
• Mentor engineers on backend best practices, distributed systems design, API architecture, and technical decision-making
• Build robust observability into backend services—measuring, debugging, and improving performance, reliability, and data freshness across the entire search stack

Requirements

• Proven track record of owning and scaling complex, high-traffic backend platforms with deep expertise in distributed systems design and long-term architectural thinking
• Deep hands-on expertise with C# / .NET or comparable backend frameworks, with a focus on performance optimization, concurrency, and service-oriented architecture
• Significant experience designing and operating large-scale data pipelines, ingestion systems, or stream-processing workflows
• Strong experience with AWS services and cloud-native infrastructure patterns — ECS, Lambda, DynamoDB, SQS/SNS, Kinesis, OpenSearch, S3, and similar
• Familiarity with search technologies, vector databases, embedding models, and ML model serving, with a strong understanding of how to operate these at production scale
• Experience designing systems for high availability, fault tolerance, and graceful degradation in latency-sensitive environments
• Strong communication skills that align engineering, product, data science, and infrastructure stakeholders around shared goals
• Passion for mentoring engineers, setting engineering best practices, and raising the overall technical quality bar

Nice-to-Haves

• Experience with vector retrieval, cross-encoder reranking, real-time ingestion, and indexing pipelines
• Background integrating ML model serving, embeddings, and LLM-driven flows into production backend systems