K
Komodo Health
Staff Software Engineer (Query Engine [Rust])
Skills
SQL QueriesRustData EngineeringPythonData ScienceSnowflakeData AnalysisMachine LearningAI
16 hours ago
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Important information
Contract type:
Permanent
Salary:
$196,000 – $265,000 / year
Location:
United States
Work mode:
Onsite
Published on:
22 October 2026
What they need
- Data Foundations builds the data products behind Komodo’s Healthcare Map, the industry’s most comprehensive source of de-identified patient data, with more than 1 trillion linked events
- We build Burrow, our query and indexing engine, written in Rust
- Burrow powers Komodo’s applications today, and soon Marmot, our AI platform, returning patient populations in under 300 milliseconds
- That’s fast enough to feel instant, and no other healthcare data analytics platform responds at that speed
- We are a small, senior, hands-on team that builds with AI tools every day
- This role exists to design, build, and scale Burrow as it becomes the engine behind more of Komodo’s products
- As a Staff-level IC, you’ll set technical direction for how the engine stores, indexes, and serves data, and for the APIs that our applications and AI agents rely on
- You will partner with Product, Platform, and Labs@Komodo (our applied AI team) to keep Healthcare Map data fast, cost-efficient, and reliable at enterprise scale
- Komodo Health uses modern engineering and AI to tackle healthcare’s biggest challenges, turning extraordinary amounts of data into meaningful insights
- In this role, you’ll build the core of Komodo’s platform and help shape a culture of technical excellence and transparency
- Query Engine Development: Design, build, and optimize Burrow’s distributed query execution, indexing, and storage layers, powering customer-facing APIs, Komodo’s software applications, and Marmot
- AI & Agentic Serving: Design the query APIs, semantic layer, and serving patterns that Komodo’s AI products and agents depend on, partnering closely with Labs@Komodo
- Scalable Data Systems: Design and implement high-performance data processing and serving patterns across large-scale healthcare datasets, with Rust as the primary language, alongside SQL, Python, DuckDB, or Spark where each is the right tool
- Query Capability Expansion: Extend Burrow beyond patient-centric data, adding healthcare provider data and new query types such as provider-level trends and top-K analytics
- Ingest & Consumer Partnership: Partner with upstream data engineering teams on how data enters Burrow, and with the products and platforms built on it, including Marmot, to deliver the APIs and queries they need
- Cross-Functional Product Delivery: Partner with Product, Data Science, Labs@Komodo, Quality, Platform, and application teams to translate complex healthcare use cases into production-grade technical designs and execution plans
- Technical Leadership: Lead complex, multi-quarter initiatives, making clear trade-offs across performance, scalability, maintainability, cost, reliability, and time-to-market
- Quality, Observability & Trust: Define and implement data quality checks, validation frameworks, observability, lineage, monitoring, and alerting to ensure Healthcare Map products and AI-serving data are accurate, explainable, and reliable
- Engineering Excellence & Mentorship: Raise the bar for system design, code quality, documentation, testing, CI/CD, and operational readiness across the team, and mentor engineers through design reviews, technical deep dives, pairing, and architectural guidance, helping the team make better decisions at scale
- —-Looking back on your first 12 months at Komodo Health, you’ll have accomplished…
- Engine Performance: Shipped measurable Burrow engine improvements in query latency, throughput, and cost per query through work on indexing, pruning, memory layout, and storage access patterns
- AI-Scale Serving: Scaled Burrow’s query interfaces for agent-driven traffic, keeping latency low as Komodo’s AI agents and LLM-driven products query the Healthcare Map at many times the volume of human users
- Migration Leadership: Led a major workstream moving existing query workloads from legacy systems onto Burrow without disrupting customers
- Collaborative Roadmap Delivery: Partnered across Data Product, Labs@Komodo, and Engineering to define technical requirements and deliver scalable, production-grade solutions
- Platform Hardening: Hardened Burrow’s multi-tenant query fleet, with measurable improvements in reliability, observability, failure handling, and cost efficiency
- Technical Multiplication: Mentored and up-leveled the engineering team, raising the bar for code quality, AI-augmented workflows, and system design- 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
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