Top Tech Jobs & Startup Jobs

Serve as a customer-facing fraud and identity expert across pre-sales, onboarding, and expansion. Design risk strategies and identity workflows, advise customers on fraud mitigation, coordinate technical and regulatory implementation requirements, validate milestones, and lead go-live readiness. Partner cross-functionally with Product, Engineering, Legal, and Compliance teams to accelerate deployment, adoption, and customer value.

Own a portfolio of APAC enterprise and mid-market customers, driving retention, adoption, measurable ROI, and expansion. Advise fraud, identity, AML, and compliance teams on risk strategies and workflow optimization. Monitor account health, lead executive business reviews, manage escalations, build success plans, train users, and identify renewal risks and expansion opportunities. Partner closely with Account Management, Product, Support, and Implementation teams while serving as a strategic customer advisor.

Own the enterprise architecture vision for scalable, high-performance, cost-efficient multi-tenant SaaS systems. Lead AWS cloud optimization, distributed data and AI infrastructure, architectural governance, and Architecture Review Council activities. Guide engineering teams on microservices, event-driven systems, automation, and cloud-native practices while driving GenAI adoption across the software lifecycle. Build prototypes, establish architectural standards, optimize total cost of ownership, and mentor technical leaders.

Leads enterprise architecture for scalable, multi-tenant SaaS systems and cloud-native platforms. Owns AWS architecture, distributed data pipelines, cost optimization, security, governance, and architectural standards. Drives GenAI and machine learning adoption across the software development lifecycle, builds self-service capabilities, guides engineering teams, conducts prototypes, and leads architecture reviews. Requires deep hands-on cloud, distributed systems, coding, infrastructure automation, AI/ML, and strategic technology leadership experience.

Provide technical pre-sales expertise for Jumio’s identity verification, KYC, AML, authentication, and risk management solutions. Responsibilities include consulting with prospects, leading technical presentations, responding to RFPs and RFIs, managing proofs of concept, onboarding customers through go-live, delivering customized web and mobile demos, and supporting sales, account management, product, engineering, and marketing teams.

Design, build, and scale AWS-based data pipelines supporting machine learning dataset creation, benchmarking, evaluation, and production workflows. Manage Airflow orchestration, write Python and SQL for large-scale processing, improve pipeline reliability and observability, monitor data quality and drift, troubleshoot data issues, and collaborate with ML, platform, and product teams on scalable data architecture.

Design, develop, and deploy deep learning and computer vision models for fraud detection (including deepfake and synthetic data detection). Own production models, research new algorithms, deploy on AWS SageMaker or devices, monitor model performance, and collaborate with engineers and product managers in an Agile environment.

Lead design and production of computer vision biometric systems (face detection, quality, attributes, recognition). Build/train models, implement fairness benchmarking, own end-to-end ML pipelines on AWS, optimize for low-latency inference, and mentor engineers.

Leads APAC strategic alliances and partner sales for identity verification and fraud prevention solutions. Develops partner strategy, recruits and manages resellers, ISVs, and system integrators, drives joint go-to-market initiatives, resolves channel conflicts, aligns direct and partner sales teams, and accelerates indirect revenue. Builds executive partner relationships, manages sales pipelines, coordinates cross-functional engagement, negotiates deals, and delivers quota attainment. The role requires occasional travel and experience selling into fintech, crypto, payments, and e-wallet markets.

Build and integrate ROS/ROS2 modules, collect and maintain ML training/test datasets from robots and mobile apps, implement end-to-end ML workflows, analyze data from internal databases, monitor data/model quality in production, and write maintainable Python/C++ code while collaborating across ML, engineering, product, and research teams.