Real-Time Platform Tech Lead – ML & Streaming

DataVisor; Mountain View (CA); On-site; USD 170,000 - 220,000; Full time

Benefits offered by this job

Health insurance

401(k)

Paid time off (PTO)

Equity

Job summary

DataVisor, the leading AI-powered fraud and risk platform, is building the next-generation real-time detection platform within its Platform Engineering team. You’ll shape architecture for streaming, storage, and training pipelines to enable scalable, real-time fraud detection.

The role requires hands-on leadership, mentoring, and a strong background in distributed systems, Java, Python, and SQL, with a focus on delivering robust production systems at scale.

Qualifications

• Bachelor's degree in Computer Science or a related field is required.
• 8+ years of software development experience.
• Strong verification discipline with ability to validate outputs against code, logs, and production behavior.
• Experience leading ML platforms or large-scale training pipelines is a plus.

Responsibilities

• Own the technical direction of the real-time detection platform, including streaming, storage, and training pipelines.
• Translate product and engineering roadmaps into clear technical plans, milestones, and execution priorities.
• 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 with Product, TAM, and customer-facing teams on customer-impacting issues and prioritization.

Skills

Software development

Technical leadership

Distributed systems

SQL

Education

Bachelor's degree in Computer Science

Tools

Cassandra

Yugabyte

Flink

Spark

Kafka

Spring Framework

Kubernetes

Job description

DataVisor, the leading AI-powered fraud and risk platform, is building the next-generation real-time detection platform within its Platform Engineering team. You’ll shape architecture for streaming, storage, and training pipelines to enable scalable, real-time fraud detection.

The role requires hands-on leadership, mentoring, and a strong background in distributed systems, Java, Python, and SQL, with a focus on delivering robust production systems at scale.