Top Tech Jobs & Startup Jobs

Owns DataVisor’s digital marketing channels and strategy across content, AI search visibility, SEO, website, email, paid advertising, display, and social media. The role is responsible for building authority in fraud, risk, and AML while generating inbound demo requests and sales opportunities. Success is measured through pipeline, organic traffic, AI search visibility, email and social engagement, paid efficiency, conversion rates, and attribution. This is a hands-on senior individual contributor role requiring strong B2B SaaS marketing, analytics, and campaign execution experience.

Develop and productionize fraud detection machine learning models, engineer features from large-scale behavioral and transaction data, and monitor model performance. Lead complex fraud investigations by reconstructing attacker behavior, identifying patterns, producing technical reports, and translating findings into detection improvements and customer-facing fraud trend insights. Collaborate with product, engineering, operations, legal, executives, and customers.

Drive revenue growth through reseller, referral, marketplace, banking, payments, and fintech partnerships. Own partner-sourced pipeline, ARR, quota attainment, and channel sales performance. Build enablement programs, co-selling processes, joint go-to-market plans, and ecosystem playbooks while supporting opportunity qualification and closure. Translate fraud, AML, risk, and AI platform capabilities into partner and customer value propositions, collaborating with Sales, Product, Marketing, Legal, Solutions Engineering, and Customer Success.

Lead the technical direction of a real-time fraud detection platform, including streaming, storage, machine learning training pipelines, and distributed systems. Responsibilities include architecture, coding, incident support, technical planning, mentoring, operational excellence, and collaboration with product and customer-facing teams. The role also establishes standards for AI-assisted engineering and develops LLM- and agent-based tools for engineering operations.

Build and operate production-grade AI, data, and distributed systems for fraud intelligence. Responsibilities include real-time data pipelines, high-throughput architecture, LLM-powered agentic workflows, AI tooling, rule and label automation, ML pipeline productionization, privacy safeguards, and cross-functional collaboration. The role requires strong Python engineering, distributed systems, cloud infrastructure, big data technologies, and machine learning fundamentals.

Manage and optimize GTM business systems and operational processes across Marketing, Sales, and Customer Success. Support HubSpot, CRM, marketing automation, integrations, data flows, and workflow automation. Build dashboards and executive reporting, analyze operational performance, improve data quality, and identify process efficiencies. Serve as a cross-functional resource for systems, reporting, and operational issues while using AI to enhance productivity and decision-making.

Lead and grow the Platform Engineering team to design, architect, and deliver a large-scale AI-driven fraud and risk decisioning platform. Set technical vision and roadmap, drive adoption of big data and real-time systems, collaborate with product and data science, enforce engineering rigor, and hire and develop senior engineering talent.

Serve as strategic partner to enterprise clients to drive ROI from an AI-powered fraud and AML SaaS platform. Lead onboarding, monitor detection performance, advise on ML and rule-engine strategies, coordinate with product and engineering, deliver business reviews, and educate customers on fraud/AML best practices to reduce risk and optimize operations.

Own DataVisor’s product marketing, PR, and analyst relations programs. Develop positioning, messaging, thought leadership, product assets, campaign materials, and executive communications while translating complex fraud, AML, AI, and SaaS technologies into customer-focused narratives. Collaborate across Product, Sales, Customer Success, Marketing, and leadership; manage agencies and analyst engagements; support launches and competitive intelligence; and use AI tools and agentic workflows to improve marketing productivity.

The Software Engineering Manager will lead the Platform Engineering team, managing engineers while architecting an AI-based fraud detection platform utilizing big data technologies.