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DataVisor

Tech Lead – Software Engineering

DataVisor

. Own the technical direction of the real-time detection platform, including streaming, storage, and the training pipelines that support it .

Posted 9/24/2026full-timeMountain View • California • United StatesSenior💰 $170,000 - $220,000 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates extensive experience in software development and technical leadership, with a strong focus on real-time systems, AI-assisted engineering, and operational excellence. Proven ability to mentor teams, drive technical outcomes, and ensure high standards in system design and code quality.

Highest-signal resume keywords
Java DevelopmentTechnical LeadershipReal-Time Systems DesignAI Coding Tools ProficiencyDistributed Systems Operations

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Software DevelopmentPython ProgrammingShell ScriptingSQLMultithreaded ApplicationsCassandraYugabyteFlinkSparkKafka
Soft Skills
MentoringTechnical Decision-MakingRisk ManagementCollaboration
Tools & Technologies
Spring FrameworkKubernetesAI AgentsLLM APIsGitHub Copilot
Certifications & Qualifications
Bachelor’s Degree in Computer Science
Industry Keywords
FraudRisk ManagementPaymentsFinancial ServicesMachine Learning Platforms

Tech Stack

Tools & technologies
CassandraJavaKafkaKubernetesPythonShell ScriptingSparkSpringSQL

About the role

Key responsibilities & impact
  • Own the technical direction of the real-time detection platform, including streaming, storage, and the training pipelines that support it
  • Translate product and engineering roadmaps into clear technical plans, milestones, and execution priorities
  • Proactively identify technical risks, dependencies, and trade-offs before they impact delivery
  • Lead design and architecture reviews, make technical trade-off decisions, and document the reasoning behind key decisions
  • Stay hands-on by coding, reviewing code, debugging issues, and supporting the team during production incidents
  • Mentor engineers and raise the bar for system design, code quality, operational excellence, and technical execution
  • Own the operational health of the platform, including alert quality, on-call load, incident follow-through, and root-cause prevention
  • Partner directly with Product, TAM, and customer-facing teams on customer-impacting issues, ensuring clear impact assessment, prioritization, ownership, and next steps
  • Define how the team uses AI agents and AI-assisted tools in engineering workflows, including verification standards and safe usage practices
  • Build, evaluate, and improve LLM- and agent-assisted tools for engineering and operations use cases, such as triage, root-cause analysis, alert summarization, and evaluation harnesses

Requirements

What you’ll need
  • 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 you did not personally implement
  • Deep production experience with Java, along with 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 how tools are used, how outputs are verified, and when AI-generated suggestions should be rejected
  • Strong verification discipline, with the 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: 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

Comp & perks
  • Health insurance
  • 401(k)
  • PTO
  • Equity