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indeed

Tech Lead - Software Engineering

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

Full Job Posting

Role overview

Join the Platform Engineering team building a next-generation machine learning platform for real-time fraud detection at scale.

The role combines hands-on engineering, technical leadership, mentoring, and ownership of streaming, storage, and training systems.

Responsibilities

  • Own platform technical direction and translate roadmaps into plans, milestones, and priorities.
  • Lead architecture reviews, make and document trade-offs, and proactively address risks and dependencies.
  • Code, review code, debug, and support production incidents while mentoring engineers.
  • Own operational health, including alerts, on-call load, incident follow-through, and root-cause prevention.
  • Partner with Product, TAM, and customer-facing teams to assess and resolve customer-impacting issues.
  • Define safe, verifiable AI-assisted engineering practices and build LLM- and agent-based engineering and operations tools.

Requirements

  • 8+ years of software development experience and 2+ years of technical leadership experience.
  • Demonstrated 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, SQL, and 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 standards for safe use and output verification.
  • Bachelor’s degree in Computer Science or a related field.

Preferred qualifications

  • Preferred: fraud, risk, payments, financial services, or another domain where false negatives have significant impact.
  • Preferred: ML platforms or large-scale training pipelines, Kubernetes, LLM APIs, agent frameworks, tool calling, RAG, or MCP.
  • Preferred: evaluations or regression tests for non-deterministic systems, hiring or mentoring engineers, and test-driven development.

Compensation and benefits

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

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