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As a Staff Software Engineer, you will lead the design and development of core systems for Confido, focusing on scalable infrastructure for financial data processing and deep technical ownership in product initiatives.

The Enterprise Account Executive will manage the full sales cycle, become a CPG expert, and build relationships with decision makers. Expect to close significant deals and travel regularly for customer engagement.

As a Senior AI/ML Engineer, you will manage the AI/ML lifecycle, develop predictive models, conduct anomaly detection, and integrate AI capabilities into the Confido platform.

As a Senior Software Engineer at Confido, you will build core infrastructure for financial workflows, develop backend services, and implement AI-powered systems for analytics and data processing, while collaborating closely with product teams and customers.

First engineering manager for a fast-growing CPG-focused AI infrastructure company. You'll manage 6–10 engineers, own team delivery and hiring, shape org design and career ladders, stay close to code across Rails/TypeScript/React/Python systems, and grow future leaders while keeping processes lightweight.

Founding product marketer who defines positioning, messaging, and GTM for an AI-powered CPG platform. Own product launches, customer insights, enablement, case studies, and integrated plans linking roadmap to marketing. Measured on deal velocity, win rate, influenced pipeline, launch impact, and enablement effectiveness.

Lead strategic finance, FP&A, and reporting initiatives; build financial models for pricing, market sizing, and unit economics; partner with Revenue on forecasting and ROI analysis; create investor and board materials; run ad-hoc strategic analyses and collaborate with data/engineering to build financial insights infrastructure.

The role involves identifying potential accounts, sending outbound messages, and enhancing the technical infrastructure. Candidates should have experience in sales or consulting, strong analytical skills, and the desire for career growth.

Design, build, and productionize core AI systems for document understanding, forecasting, and agentic workflows. Handle messy data ingestion, evaluation, monitoring, anomaly detection, entity reconciliation, and backtesting to deliver reliable, product-focused ML solutions.

Design, build, and maintain a centralized data warehouse and analytics platform. Create scalable data models, ETL/ELT pipelines, and semantic layers. Improve data quality, governance, lineage, and accessibility. Partner cross-functionally to define metrics, enable self-service analytics, and standardize data models across products and teams.