Senior Software Engineer, Data Infrastructure (RDBMS) at TRM Labs

Build a Safer World. TRM Labs provides AI-powered intelligence solutions that help public and private sector agencies investigate and disrupt crime. TRM's platforms enable investigators to trace illicit activity, build cases, and construct operating pictures of threat networks. Leading agencies and businesses worldwide rely on TRM to make the world safer and more secure. The Data Platform team builds and owns highly available, scalable data infrastructure for TRM's products and services. As a Senior Software Engineer on Data Infrastructure (RDBMS), you will develop, operate, and scale the relational database systems that serve data at petabyte scale, helping build a safer financial system for billions of people. This role is uniquely broad at TRM: you own the serving layer end to end, from query performance to cost to availability, on infrastructure that product teams depend on every day. The impact you will have: Keep customer-facing APIs fast and available at five-nines by owning query tuning, index design, and schema optimization on petabyte-scale Postgres/Citus, directly determining whether product teams can serve data in real time Cut storage and compute costs materially by using AI-assisted analysis (pganalyze paired with Claude) to detect compression and data-model opportunities, then shipping validated changes to production Remove team toil by building agentic automation for routine database operations, such as self-serve pgbouncer provisioning, disk scaling, and blue-green deployments, so any engineer can run them safely Protect data integrity and latency by driving agentic validation of database changes before they reach production Keep real-time data flowing by managing CDC pipelines (PeerDB, Fivetran, Debezium) and using AI tooling to debug replication failures faster Shape the next-generation platform by migrating workloads off first-gen infrastructure and prototyping new data stores with AI-accelerated spikes Raise the whole team's leverage by codifying your workflows into AI-native runbooks and internal tooling that teammates reuse What we're looking for: 5–8 years building and operating production PostgreSQL (Citus, Aurora, AlloyDB, or equivalent distributed Postgres) Deep SQL optimization skills (Explain Plans, CTEs, window functions, partitioning, index design, query-planner behavior in distributed environments), increasingly paired with AI-assisted query analysis Hands-on experience with CDC tools (PeerDB, Fivetran, Debezium, Datastream, Airbyte) and comfort using AI tooling to debug replication failure modes Fluency with database profiling (pganalyze or equivalent) to interpret metrics and logs, including using LLMs to summarize performance findings Production automation experience in Python or Go, including agentic automation of routine database tasks; Postgres extension development is a plus Daily use of AI coding tools (Claude, Copilot) to accelerate development and produce higher-quality output faster, with the judgment to