Senior Backend Engineer
LINDA S. LEVINE
San Francisco, CA, United States
about 2 months ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
6 years minimum
Working hours
Regular working hours
Job source
Tech stack
Application Programming Interfaces (APIs)
Airflow
Encodings
Databases
Distributed Systems
Online Analytical Processing
Pattern Recognition
Query Optimization
Management of Software Versions
Web Services
Large Language Models
Apache Spark
+9 more
Backend
Data Layers
Build Management
Apache Flink
Apache Kafka
Presto
Vertica
Api Design
Stream Processing
Job description
We’re looking for a Senior Backend Engineer to own the services and APIs that power the data layer. You’ll design the systems that ingest, evaluate, and serve agent telemetry at scale., * Design and build high-throughput backend services that ingest and process hundreds of thousands of agent traces per second.
- Own the API surface our SDKs and dashboards depend on: define contracts, manage versioning, and keep latency low under real customer load.
- Tune our OLAP layer (ClickHouse) through schema design, query optimization, and access-pattern analysis so reads stay fast as data grows to petabyte scale.
- Partner with the platform and infra teams on scalability, reliability, and the systems that back our evaluation and monitoring pipelines.
- Advocate for a high bar on backend and engineering quality: reliable, efficient, well-documented, testable, and maintainable.
Requirements
Do you have experience in Web services design?, * 6+ years of relevant industry experience building and operating high-throughput backend systems and services.
- Strong fundamentals in API design, data modeling, and the trade-offs of distributed systems under real production load.
- Hands-on experience with OLAP / columnar databases (ClickHouse, Presto) and a feel for how query patterns map to storage internals.
- Experience designing high-performance distributed systems.
- Comfort across the stack, with the breadth to reason about platform and infra decisions.
- Strong communication skills. You write clearly, review well, and make the people around you better., * Experience scaling pipelines that fan out to LLM APIs and managing the rate-limit, retry, and cost dynamics that come with them.
- Familiarity with streaming systems (Kafka, Spark, Flink, Ray) and ML orchestration tools (Airflow, Dagster, Prefect).
- Background in embedding / vector search infrastructure or data quality monitoring.
- Prior work on observability or developer-facing platform products.
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