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TRM Labs

Blockchain analytics for financial crime

Senior Software Engineer - Data Infrastructure, RDBMS

Database AdministrationConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • Five to eight years of experience building and operating production PostgreSQL, including Citus, Aurora, AlloyDB, or equivalent distributed PostgreSQL.
  • Deep SQL optimization skills, including Explain Plans, common table expressions, window functions, partitioning, index design, and query-planner behavior in distributed environments, increasingly paired with AI-assisted query analysis.
  • Hands-on experience with change data capture tools such as PeerDB, Fivetran, Debezium, Datastream, or Airbyte, and comfort using AI tooling to debug replication failure modes.
  • Fluency with database profiling tools such as pganalyze or equivalent to interpret metrics and logs, including using large language models to summarize performance findings.
  • Production automation experience in Python or Go, including agentic automation of routine database tasks.
  • Daily use of AI coding tools such as Claude or Copilot to accelerate development and produce higher-quality output, with judgment to know when to trust or reject AI output.
  • A track record of using AI-assisted analysis to drive measurable cost or performance improvements in production database systems.
  • Participation in an on-call rotation approximately once every 15 days, with each shift a 24-hour window across two days.

Responsibilities

  • Develop, operate, and scale relational database systems that serve data at petabyte scale.
  • Keep customer-facing APIs fast and available by owning query tuning, index design, and schema optimization on petabyte-scale Postgres and Citus.
  • Use AI-assisted analysis with pganalyze and Claude to identify compression and data-model opportunities, then ship validated changes to production to reduce storage and compute costs.
  • Build agentic automation for routine database operations, such as self-serve pgbouncer provisioning, disk scaling, and blue-green deployments.
  • Drive agentic validation of database changes before they reach production to protect data integrity and latency.
  • Manage change data capture pipelines using PeerDB, Fivetran, and Debezium, and use AI tooling to debug replication failures.
  • Migrate workloads off first-generation infrastructure and prototype new data stores using AI-accelerated spikes.
  • Codify workflows into AI-native runbooks and internal tooling for teammates to reuse.
  • Within 30 days, ship self-serve scaling automation for pgbouncer provisioning and disk resizing to eliminate a single point of failure.
  • Within the first quarter, identify and validate a compression opportunity using AI-assisted analysis and ship it to production for measurable storage-cost reduction with no availability impact.
  • Within 90 days, coordinate a schema change across three product-engineering teams in parallel and deliver platform changes ahead of a product deadline.
  • Participate in in-person R&D work weeks, typically one to two times per quarter, at a TRM hub or other designated location; additional travel may be required based on team and cross-functional needs.

Desired Qualifications

  • PostgreSQL extension development experience.

About the Company

TRM Labs

Blockchain analytics for financial crime

TRM Labs provides blockchain intelligence tools for financial institutions, crypto businesses, and government agencies to detect and investigate crypto-related financial crime and fraud. It analyzes blockchain activity using data engineering, data science, and threat intelligence to surface risk signals, enable investigations, and support compliance workflows. Its products combine on-chain and off-chain data, risk scoring, and case management through subscription services and customized solutions. Compared to others, TRM Labs serves a diverse client base (banks, exchanges, regulators) and emphasizes end-to-end investigative capabilities and tailored risk insights rather than generic analytics. The company’s goal is to improve the security and integrity of the global financial system by reducing illicit activity in the crypto space.

Company size
201-500
Company stage
Series C
Total funding
$220M
Headquarters
San Francisco, CA
Founded
2018

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