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Tech Lead - Software Engineering

DataVisor
Vancouver, CAN
Full-time
Onsite
$130,000–$170,000,
Discovered 1 months ago
JavaPythonShell scriptingDistributed real-time systemsRelational databasesSQL

Full Job Posting

About DataVisor

DataVisor provides an AI-powered fraud and risk platform for fraud and anti-money-laundering use cases.

Its platform uses machine learning, device intelligence, decisioning, and investigation tools for real-time detection.

Role overview

The Platform Engineering team develops a machine learning platform combining proprietary unsupervised and supervised learning for real-time fraud detection.

The role leads streaming systems, storage layers, and training pipelines, while remaining hands-on and mentoring engineers.

Responsibilities

  • Own technical direction for real-time detection, streaming, storage, and training pipelines; turn roadmaps into plans and milestones.
  • Identify risks and trade-offs; lead architecture reviews, make decisions, and document rationale.
  • Code, review, debug, support incidents, mentor engineers, and improve design, quality, and execution.
  • Own operational health, alerts, on-call load, incident follow-through, and root-cause prevention.
  • Partner with Product, TAM, and customer-facing teams to assess and prioritize customer-impacting issues.
  • Define safe AI-assisted engineering standards and build/evaluate LLM tools for triage, root-cause analysis, alert summaries, and evaluation.

Required qualifications

  • 8+ years of software development experience and 2+ years of technical leadership experience.
  • Ability to lead team technical outcomes, including work not personally implemented.
  • Deep production Java experience; 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 with multithreaded and concurrent applications.
  • Hands-on experience with Cassandra, Yugabyte, Flink, Spark, or Kafka; experience with Spring Framework.
  • Production use of AI coding tools and ability to set team standards for their use and verification.
  • Ability to validate model outputs against source code, logs, documentation, and production behavior.
  • Bachelor’s degree in Computer Science or a related field is required.

Preferred qualifications

  • Experience in fraud, risk, payments, financial services, or another high-impact false-negative domain.
  • Experience owning ML platforms or large-scale training pipelines; Kubernetes experience.
  • Experience with LLM APIs, agent frameworks, tool calling, RAG, or MCP; evaluation or regression testing for non-deterministic systems.
  • Experience hiring, managing, or mentoring engineers; test-driven development experience.

Compensation and benefits

  • Base salary range is CAN $130,000–$170,000, commensurate with experience.
  • Benefits include health insurance, paid time off, and equity.

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