Senior Software Developer leading scalable software application development, mentoring engineers, and aligning technical solutions with business needs. Improving delivery through coding standards, DevOps, automation, and CI/CD.
About the role
- Tech Lead directing streaming, storage, and training systems for DataVisor’s AI-powered fraud and risk platform. Leading distributed systems execution and AI-assisted engineering practices.
Responsibilities
- Own the technical direction of the real-time detection platform, including streaming, storage, and training pipelines
- Translate product and engineering roadmaps into technical plans, milestones, and execution priorities
- Identify technical risks, dependencies, and trade-offs before they impact delivery
- Lead design and architecture reviews, make technical trade-off decisions, and document key decisions
- Code, review code, debug issues, and support the team during production incidents
- Mentor engineers and raise standards for system design, code quality, operational excellence, and technical execution
- Own platform operational health, including alert quality, on-call load, incident follow-through, and root-cause prevention
- Partner with Product, TAM, and customer-facing teams on customer-impacting issues
- Define team standards for AI agents and AI-assisted engineering workflows, including verification and safe usage practices
- Build, evaluate, and improve LLM- and agent-assisted tools for triage, root-cause analysis, alert summarization, and evaluation harnesses
Requirements
- 8+ years of software development experience
- 2+ years of technical leadership experience as a tech lead, staff engineer, engineering manager, or similar role
- Proven ability to lead technical outcomes across a team, including work not personally implemented
- Deep production experience with Java
- Working proficiency in Python and Shell scripting
- Experience designing, building, shipping, and operating distributed real-time systems at scale
- Strong knowledge of computer systems, relational databases, and SQL
- Experience building and optimizing multithreaded and concurrent applications
- Hands-on experience with Cassandra, Yugabyte, Flink, Spark, or Kafka
- Experience with the Spring Framework
- Demonstrated use of AI coding tools such as Claude Code, Cursor, GitHub Copilot, or similar tools in real production work
- Ability to set team-level standards for AI-assisted engineering, including tool usage, output verification, and rejection of AI-generated suggestions when appropriate
- Strong verification discipline, including validating model outputs against source code, logs, documentation, and production behavior
- Bachelor’s degree in Computer Science or a related field is required
- Preferred: experience in fraud, risk, payments, financial services, or another domain where false negatives carry significant business or customer impact
- Preferred: experience owning ML platforms or large-scale training pipelines
- Preferred: experience with Kubernetes
- Preferred: experience building with LLM APIs, agent frameworks, tool calling, RAG, or MCP
- Preferred: experience writing evaluations or regression tests for non-deterministic systems
- Preferred: experience hiring, managing, or mentoring engineers
- Preferred: experience with test-driven development
Benefits
- Health insurance
- PTO
- Equity
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