DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry.With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time.Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one.DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership compared to legacy point solutions.DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven.Come join us!

Role Summary

We are hiring a Software Engineer to build the automation that lets a small team deliver fraud and AML solutions to many clients at once.

You will build internal tooling the Solutions team uses every day — Claude Code plugins, skills and MCP servers in our internal plugin marketplace — and integrate them with our AI Sandbox, the Vera platform, and the APIs behind them. You will also work directly on client onboarding: standing up tenants from solution templates, parsing third-party data and responses, wiring up integrations, and validating end to end that the right alerts actually fire.

This is a production software engineering role. What we are really hiring for is the instinct to turn something one client needed into something every client gets. Machine learning experience is not required, and neither is a fraud or AML background — both are learnable, and we would rather have an engineer who ships.

This role is open at both junior and senior levels.

Primary responsibilities

• Build Automation Tooling: Design and ship the plugins, skills and MCP servers the Solutions team runs — tenant creation, configuration copying, onboarding flows, on-call helpers — in Python and shell.
• Make It Reusable: Turn one-off solutions into tooling that works for every client. This is the core of the job, not an afterthought.
• Integrate with the Platform: Connect tooling to the AI Sandbox, Vera and internal platform APIs, and keep it working across sandbox, preprod and production tenants.
• Support Client Onboarding: Work hands-on on live onboardings — tenant setup from templates, schema and response parsing, third-party integrations over SFTP and API, and end-to-end validation that the right alerts fire.
• Serve Your Users: What you build is used by core engineering, product, delivery, customer support and technical account management. Understanding what each of them needs, and keeping them informed, is part of the work.
• Own Your Projects: Scope, sequence and deliver your own work, and say clearly where it stands.

Requirements

Qualifications

• Experience: At least 1 year of full-time professional software engineering experience building and shipping production systems. Internships are not counted toward this minimum. We are open on level — we care more about what you have built than how long you have been building.
• Education: BS in Computer Science, Computer Engineering, or Software Engineering. MS preferred. We also consider other STEM degrees alongside a record of shipped production software.
• Shipped Software: Demonstrated experience delivering working software end to end — not prototypes or notebooks.
• Coding Proficiency: Strong, production-grade Python — the primary language for this team's automation and tooling. Java is expected for senior candidates and preferred for junior ones: our core platform is built in Java, and you will work across both over time. Comfort with shell, and with reading unfamiliar codebases, matters as much as either language.
• Cloud and Containers: Experience with AWS and containerization (Docker/Kubernetes).
• Built for Others: Evidence of building something other people then used — an internal tool, a library, a plugin, a template, a service another team depends on.
• Collaboration and Ownership: Able to work across team boundaries, take end-to-end ownership, and operate where the path is not already defined.

Preferred qualifications

• Java, if you are applying at a junior level — our core platform is built in it.
• TypeScript — solution features often land in our front end.
• LLM-powered agent workflows — LangChain/LangGraph, multi-agent orchestration, tool calling or RAG — for production or internal platforms.
• Distributed data frameworks such as Spark, Kafka or Flink.
• Experience deploying or maintaining machine learning models in production.
• Analytical databases and large-scale data exploration (ClickHouse or other columnar stores).
• Real-time decision engines or stateful stream processing.
• Domain knowledge in fraud or risk — a plus, never a requirement.

Benefits

• Base Salary: 130K – 250K
• Total Compensation: Includes Base + Performance Bonus + Equity Options.
• Comprehensive medical, dental, and vision coverage.
• Discretionary Time Off Policy (DTO) and paid holidays.
• Opportunities for R&D exploration and professional development.
• Regular team-building events and a collaborative, innovative culture.