Senior Software Engineer Graph Analytics
Blockchain intelligence company providing tools to detect, investigate, and manage crypto-related fraud, financial crime, and compliance for institutions and government agencies.
Maintainer signals as of 9/2/2026
Funding history
Investors
About TRM Labs
TRM Labs provides blockchain intelligence for investigations and compliance, offering products such as forensics, wallet screening, entity screening, transaction monitoring, and APIs. It serves financial institutions, crypto businesses, and public sector agencies to trace funds, assess risk, and build cases across digital assets.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
Build scalable graph systems that analyze large cryptocurrency transaction networks, implement real-time graph algorithms using distributed databases and graph processors, and collaborate with engineers, data scientists, and investigators on predictive learning and risk-analysis capabilities.
Requirements
- Quantitative academic background in Computer Science, Mathematics, Engineering, Physics, or a similar field.
- Strong knowledge of algorithm design and data structures with experience applying them to real-world problems.
- Experience optimizing large-scale distributed data processing systems such as Spark, Hadoop, Dask, and distributed graph databases.
- Experience converting academic research into products and working with research teams that ship features.
- Strong programming experience with Python and SQL.
- Excellent communication skills for explaining complex topics to technical and non-technical audiences.
- Self-motivation, independent problem-solving, comfort with ambiguity, and accountability for outcomes.
- Knowledge of basic graph theory concepts.
Responsibilities
- Design and implement graph algorithms for large cryptocurrency transaction networks at multi-blockchain scale.
- Research graph-native technology for data science and data engineering applications.
- Collaborate with cryptocurrency investigators to identify user stories and requirements for graph algorithms and features.
- Understand and refine risk models that analyze cryptocurrency transaction networks and assign address risk scores.
- Communicate complex implementation details to investigators, customer success stakeholders, data engineers, and data scientists.
- Integrate diverse data inputs, including raw blockchain data and complex model outputs.
