Top Tech Jobs & Startup Jobs

Design and present transformation roadmaps, business cases, process improvements, workshops, demos, and proposals for European financial institutions. Lead customer discovery, diagnose AML/KYC, sanctions, and fraud-related needs, scope tailored AI-driven risk solutions, and support sales engagements through handoff to Customer Success. Provide market and client insights to Product and Engineering, maintain sales enablement materials, contribute to technical marketing content, and manage multiple projects while traveling across Europe.

Build and maintain platform data services and ML infrastructure powering a SaaS product. Work on Hadoop/Spark pipelines, real-time services, Kubernetes/Docker containerized microservices in Scala/Python, design scalable algorithms and ETL pipelines, write automated tests, and collaborate with data scientists, DevOps, front-end engineers, and product managers.

Design, build, and maintain Quantifind's Apache Spark batch pipelines and backend platform that generate risk signals from diverse data sources. Implement scalable algorithms, data services, ETL pipelines, and microservices; deploy on Kubernetes and optimize storage/caching and distributed processing. Collaborate with Data Scientists, DevOps, Product, and Sales to deliver performant, testable systems processing terabytes daily.

Manage and scale on-premises and cloud infrastructure using infrastructure as code, configuration management, automation, and container orchestration. Collaborate with DevOps, platform, security, data science, and product teams to improve deployments, reliability, performance, monitoring, and security. Own major infrastructure projects, support compliance requirements, mentor engineers, and operate systems across company data centers and AWS.

Design enterprise, data-heavy product surfaces from research through high-fidelity specs. Lead features, run customer sessions, improve workflows and data visualizations, scale the design system, and collaborate with Product and Engineering. Leverage AI tools to accelerate research and prototyping.

Own the product strategy and roadmap for machine-learning-powered core models. Translate customer needs into model objectives, evaluation criteria, thresholds, requirements, and acceptance criteria. Partner with Data Science and Engineering to deliver and improve models, assess performance, document capabilities and limitations, support customer evaluations, and manage model risk requests. Serve as a customer-facing subject matter expert while driving measurable outcomes and executive alignment.

Lead end-to-end technical software implementations, translate business requirements into development initiatives, manage cross-functional teams, track risks/issues and project financials, define requirements and milestones, and report progress to stakeholders and senior leadership to ensure timely, high-quality delivery.

Build responsive browser-based applications using React, Redux, JavaScript, HTML, and CSS. Develop reusable components, data visualizations, REST API integrations, unit and integration tests, and maintainable code for continuous delivery. Collaborate with Design, DevOps, Product, Data Science, and platform engineering teams in an Agile environment to deliver customer-facing risk visualization features.

Develop machine learning and data science solutions for financial crime risk management. Responsibilities include analyzing large datasets with SQL, Python, and PySpark; designing ETL pipelines; training supervised and unsupervised models; implementing solutions in Scala; applying LLMs and NLP; supporting customer proofs of concept; and collaborating with product and platform teams in an agile environment.

Solutions Consultant responsible for designing, configuring, and presenting AI-driven risk management solutions to financial institutions and government clients. The role involves customer discovery, solution design, business case development, executive workshops, proposals, demos, implementation planning, and cross-functional collaboration with Product, Engineering, Marketing, and Customer Success. Candidates should understand AML, KYC, sanctions, fraud, and financial institution workflows, while articulating measurable business value and supporting sales engagements through production.