Release Engineer, DataVisor
CA$70-90k
ML-powered fraud detection
Be an early applicant
ML-powered fraud detection
101-200 employees
Be an early applicant
CA$70-90k
101-200 employees
Company mission
To deliver the world’s most sophisticated AI-powered solutions to keep companies and their customers safe from fraud and abuse.
Role
Who you are
- 1–3 years of experience in software engineering, DevOps, or release engineering roles
- Bachelor’s degree in Computer Science, Software Engineering, or a related STEM discipline, or equivalent experience in a software engineering environment
- Know CI/CD systems (e.g., Jenkins, GitLab CI, GitHub Actions, or similar)
- Proficiency in Python for developing automation scripts, integration tools, and release management utilities
- Solid understanding of build automation, test automation, and deployment pipelines for enterprise software
- Experience with cloud platforms (AWS, GCP, or Azure) and container technologies such as Docker and Kubernetes
- Proficient with version control systems (e.g., Git) and branch management strategies (release/hotfix/cherry-pick workflows)
- Strong analytical and problem-solving skills, with the ability to identify inefficiencies and implement automation improvements
- Excellent communication and collaboration skills to work effectively with developers, QA, operations, and management teams
- Highly organized, detail-oriented, and self-motivated, with a strong sense of ownership and accountability
- Passionate about automation, reliability, and continuous improvement in software delivery processes
What the job involves
- Tool Builder: Develop and maintain internal automation tools or scripts (primarily in Python) to support release management, streamline build/deployment workflows, and improve release visibility and traceability
- CI/CD Owner: Design, maintain, and optimize CI/CD pipelines to enable reliable, automated build, test, and deployment processes across all environments
- Release Executor: Collaborate with development, QA, and infrastructure teams to ensure successful and timely code releases, including version control, branch management, and code cherry-picks
- Quality Gatekeeper: Validate build integrity, coordinate pre-release testing, and ensure all deployments meet stability and performance standards before production rollout
- Issue Resolver: Proactively troubleshoot CI/CD and automation tool issues, coordinate with cross-functional teams to resolve build or deployment failures, and continuously improve pipeline reliability
- Incident Support: Participate in incident response during and after releases, manage rollback procedures when necessary, and contribute to postmortem analysis for future prevention
- Metrics Contributor: Monitor and analyze release metrics (build success rates, deployment durations, rollback frequencies, etc.) and provide insights for process improvement
- Release Process Coordinator: Partner with the Release Manager to align release schedules, manage change control, and document release notes, change logs, and deployment procedures
- Cross-Team Collaborator: Work closely with developers, QA, SREs, and PMs to streamline workflows, ensure smooth delivery of features, and maintain high release reliability
- Documentation and Compliance: Maintain detailed release documentation, version tracking, and audit trails to support transparency, compliance, and operational excellence
Our take
As the use of online shopping and banking continues to rise, so too does the opportunity for fraud, with criminals exploiting the gaps in defences that come with an increasingly novel digital environment. DataVisor provides the leading fraud detection solution that leverages machine learning to identify threats, to overcome the security gap caused by the speed at which today’s digital fraudsters evolve.
Traditional fraud solutions have not been designed to handle digital data, and they are especially ill-equipped to deal with quickly changing environments. By employing advanced ML, DataVisor can identify the patterns which allude to fraudulent behaviour, allowing organisations to respond immediately and prevent losses before they happen. Another problem with some systems has been that, in the name of security, they might delay ultimately good customers from accessing services. With DataVisor this becomes a non-issue, as the pattern of a non-malicious user can also be identified with speed.
DataVisor has seen considerable investment - that will fuel its continued expansion across the globe - and has an impressive list of customers. The company has also made several partnerships that will act towards strengthening its product offering. For example, it is extending its analytics and fraud detection through partnership with Equifax, by gaining access to its rich consumer identity data.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 3 rounds)
Dec 2022
$40m
LATE VC
Feb 2018
$40m
SERIES C
Total funding: $94.5m
Company benefits
- Stock Options
- Commuter Passes
- Paid Time Off
- Catered Lunch and Dinner
- Team and Company Outings
Company HQ
Mountain View, CA
Leadership
Yinglian Xie
(CEO)Extensive experience in security and AI. Previously a Senior Researcher at Microsoft Research.
Fang Yu
(CPO)Former Senior Researcher at Microsoft Research, with vast experience in big-data algorithms.
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