Staff Software Engineer (Query Engine [Rust])

Join Komodo Health, a leading healthcare data analytics platform, as a Staff Software Engineer. In this role, you will design, build, and scale Burrow, our query and indexing engine, which powers our applications and AI platform. You will set the technical direction for data storage, indexing, and serving, and collaborate with cross-functional teams to deliver scalable, production-grade solutions. This is an opportunity to make a significant impact on healthcare by turning vast amounts of data into meaningful insights.

• Design, build, and optimize Burrow's distributed query execution, indexing, and storage layers, powering customer-facing APIs and applications.
• Partner with Product, Platform, and Labs@Komodo to keep Healthcare Map data fast, cost-efficient, and reliable at enterprise scale.
• Lead complex, multi-quarter initiatives, making clear trade-offs across performance, scalability, maintainability, cost, reliability, and time-to-market.

• AI-Augmented Engineering: Hands-on use of AI tools such as ChatGPT, Gemini, Cursor, Claude, or similar to improve engineering productivity, design quality, testing, documentation, and decision-making. You'll actively experiment with new AI techniques, share learnings across teams, and contribute to Komodo's AI-first engineering culture
• Systems Programming Depth: Experience writing high-performance systems code in Rust (strongly preferred) or Erlang or C++, owning services end to end, including operating them in production
• Performance Engineering: Comfort profiling and tuning distributed systems across memory, CPU, I/O and NVMe access patterns, caching, partitioning, and failure handling at fleet scale
• Real-Time and/or AI/ML Enablement: Experience building query or serving infrastructure consumed by AI/ML systems, LLM-driven products, or high-volume real-time traffic
• Architecture & Systems Design: Demonstrated ability to design data models, serving patterns, platform components, and system architectures for complex, high-volume data environments
• Staff-Level Technical Leadership: Track record of setting technical direction beyond your own team: leading design reviews, mentoring senior engineers, and driving multi-quarter architecture decisions across teams
• Query Engine & OLAP Internals: Deep knowledge of how analytical engines work under the hood: columnar formats (Parquet, Arrow), indexing and pruning (bloom filters, star-tree, and similar), compression and compaction, query planning and execution, and low-latency, high-RPS serving. Experience building on or extending engines such as Pinot, Druid, ClickHouse, DuckDB, DataFusion, or Trino
• Technical Communication: Ability to explain technical decisions, trade-offs, risks, and delivery status clearly to engineers, product partners, data scientists, AI engineers, and senior stakeholders
• Healthcare Data Experience: Experience with claims, clinical, RWE, provider, patient, or life sciences data, including familiarity with coding systems such as ICD-10, CPT, NDC, RxNorm, NPI, or taxonomy data. Not required; strong engine engineers ramp quickly
• Warehouse-to-Engine Migrations: Experience moving workloads off Redshift, Snowflake, or similar warehouses onto purpose-built serving infrastructure
• High-Scale Data Architecture: Experience designing systems for large-volume data processing, productization, versioning, delivery, performance optimization, and cost efficiency, including newer columnar formats like Vortex
• Applied AI / Agentic Workflows: Experience using, designing, or integrating AI-enabled workflows — including LLM pipelines, multi-agent orchestration, prompt chains, or evaluation frameworks — to improve data quality, extraction, curation, or product delivery
• Fast-Growth Execution: Experience operating in high-growth or ambiguous environments where technical leaders must balance architecture, delivery, quality, and speed