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Salary: USD 200,000 - 220,000 / annual
TRM Labs provides AI-powered intelligence solutions that help public and private sector agencies investigate and disrupt crime. 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 relational database systems serving data at petabyte scale. This role is uniquely broad: you own the serving layer end to end, from query performance to cost to availability, on infrastructure that product teams depend on daily.
Key responsibilities include:
- 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 workflows into AI-native runbooks and internal tooling that teammates reuse
The Data Platform team is distributed across US and Canada, operating async-first with intentional synchronous touchpoints. Team culture is product-focused, customer-focused, coaching-oriented, scrappy when needed, and process-oriented. You will work alongside senior engineers who care deeply about their craft and hold high standards for code quality, operational excellence, and cross-team communication.
On-call rotation: approximately once every 15 days; each shift is a 24-hour window across 2 days. On-call is confirmed for United States; Canada portion pending regional compliance review.
Expected impact milestones:
- Within 30 days: eliminate a single point of failure by shipping self-serve scaling automation
- Within first quarter: identify a compression opportunity with AI-assisted analysis and ship to production for measurable storage-cost reduction
- Within 90 days: coordinate a schema change across three product-engineering teams and deliver platform changes ahead of a product deadline
REQUIREMENTS:
- 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 know when to trust or reject AI output
- Track record of using AI-assisted analysis to drive measurable cost or performance improvements in production database systems
