Tech Lead of Software Engineering

DataVisor

As part of the Platform Engineering team, you will help build DataVisor’s next-generation machine learning platform, combining our proprietary unsupervised machine learning technology with supervised machine learning algorithms to power real-time fraud detection at scale
As fraud attacks become increasingly sophisticated, real-time detection is more critical than ever
Our platform team is responsible for designing and developing the architecture that makes scalable, real-time detection possible, including streaming systems, storage layers, and training pipelines that support our core detection capabilities
We are looking for a creative, hands-on engineering leader to help expand our streaming and database systems, improve our core detection algorithms, and automate the end-to-end training process
This role is ideal for someone who enjoys solving complex distributed systems problems, mentoring engineers, and driving technical execution in a high-impact environment
Join us as we continue to push the boundaries of fraud detection, machine learning infrastructure, and large-scale data processing
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

Benefits

Stock Options
Commuter Passes
Paid Time Off
Catered Lunch and Dinner
Team and Company Outings

Demonstrated use of AI coding tools such as Claude Code, Cursor, GitHub Copilot, or similar tools in real production workStrong knowledge of computer systems, relational databases, and SQLAbility 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 rejectedBachelor’s degree in Computer Science or a related field is requiredExperience with the Spring FrameworkExperience designing, building, shipping, and operating distributed real-time systems at scaleProven ability to lead technical outcomes across a team, including work you did not personally implementExperience building and optimizing multithreaded and concurrent applications2+ years of technical leadership experience as a tech lead, staff engineer, engineering manager, or similar roleHands-on experience with Cassandra, Yugabyte, Flink, Spark, or KafkaStrong verification discipline, with the ability to validate model outputs against source code, logs, documentation, and production behavior8+ years of software development experienceDeep production experience with Java, along with working proficiency in Python and Shell scriptingExperience in fraud, risk, payments, financial services, or another domain where false negatives carry significant business or customer impactExperience owning ML platforms or large-scale training pipelinesExperience with KubernetesExperience writing evaluations or regression tests for non-deterministic systemsExperience building with LLM APIs, agent frameworks, tool calling, RAG, or MCPExperience hiring, managing, or mentoring engineersExperience with test-driven development

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Vacancy posted 14 hours ago

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