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Senior Backend Engineer (Agentic Data Platform)

Sequencing

  • United States, United States · Lakin, Kansas, United States · Berkeley, California, United States
  • Remote
  • Posted Aug 10, 2026
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DuckDBTypeScriptAWS SQSApache SparkQdrantDistributed SystemsRedisData ProcessingRabbitMQPostgreSQLBullMQ

Job description

About the role

The Senior Backend Engineer will design, build and improve the high‑throughput, fault‑tolerant distributed backend systems that power Sequencing’s genomics platform and its AI‑driven natural language interface, collaborating with the AI Backend Architect, bioinformatics experts and product/design teams to deliver fast, accurate and reliable genetics‑based guidance.

About the company

Sequencing builds the interface between humanity and its DNA using clinical‑grade whole genome sequencing, AI and a growing ecosystem of genomic applications. As the world’s largest direct‑to‑consumer whole‑genome sequencing platform, the profitable, venture‑backed, fully remote company aims to turn the human genome into a lifelong source of personalized guidance and become the trusted home for every genome on Earth.

Requirements

  • 5+ years building and operating production backend systems at scale.
  • Expert‑level proficiency in TypeScript, capable of owning production services end‑to‑end.
  • Strong fundamentals in distributed systems design and failure modes.
  • Hands‑on experience with large‑scale data processing frameworks (Apache Spark or equivalent) and very large datasets.
  • Deep familiarity with both OLTP and OLAP data systems (PostgreSQL, DuckDB).
  • Solid experience with distributed event‑driven systems.
  • Ability to quickly learn and work in an unfamiliar domain such as genomics.
  • Craft‑driven mindset with attention to detail and high quality standards.
  • Eligible to work remotely in time zones UTC‑5 to UTC+3.
  • Experience with Rust and functional programming (Scala or similar).
  • Python for data processing.
  • Experience training or fine‑tuning your own AI models.
  • Experience with multi‑agent AI systems and orchestration (planner/router/evaluator patterns).
  • Production experience with LLM APIs (Anthropic, OpenAI, Bedrock, Google AI).
  • Production experience with vector databases and RAG pipelines.
  • Familiarity with LLM observability tooling (Langfuse, LangSmith).
  • Experience with workflow engines (Temporal).
  • Knowledge of genomics, bioinformatics, or health data systems.
  • High‑growth startup experience.