Top Tech Jobs & Startup Jobs

Build and automate AI-driven marketing workflows end-to-end. Own lead scoring, routing, campaigns, content production, events, and reporting. Maintain marketing data integrity, manage HubSpot/Salesforce integrations, develop playbooks for AI tools, and create dashboards to measure marketing ROI and pipeline performance.

The Data Platform Engineer will design and implement ETL pipelines, develop APIs for data retrieval, and manage scalable storage, contributing to backend engineering efforts and data product development.

Lead and scale a Support Engineering team handling complex API and payments issues, own incident response and SLAs, build operational processes, drive metrics and automation, partner cross-functionally, and hire and develop team members.

Lead RevOps analytics and GTM engineering to scale revenue processes. Build analytics infrastructure, evaluate AI-first tech, automate lead-to-cash workflows using AI-assisted development, integrate systems, and deliver data-driven strategic insights across Sales, Marketing, and Post-Sales.

As a Data Scientist, you will design and deploy data-driven fraud prevention solutions, working directly with clients to tackle unique challenges. You'll build machine learning models and collaborate with engineering to enhance backend systems.

The Support Engineer will provide technical support and customer assistance for the platform, troubleshoot issues, and collaborate with internal teams to enhance customer satisfaction and product quality.

As an FP&A Analyst, you'll manage budget analysis, partner with departments on financial planning, develop operating models, and leverage AI for financial insights.

Own and evolve DevOps and platform engineering: build and maintain CI/CD pipelines, improve observability (Datadog/Prometheus), implement FinOps governance and cost optimization, manage IaC and Kubernetes tooling, enable developer productivity, define SLOs, and collaborate cross-functionally on security and financial alignment.

Sell Sardine's fraud and AML platform to Fortune 1000, financial institutions, fintechs and neo-banks. Build and qualify pipeline, run discovery, tailor demos with Solutions Engineering, manage complex multi-threaded sales cycles, lead negotiations and contracting, cultivate executive relationships across risk, compliance and technology, and provide market feedback to cross-functional teams.

Design and build end-to-end ML systems for fraud detection: develop and deploy models, create production-ready features and real-time data pipelines, integrate with backend services, and ensure monitoring, security, and observability.