Top Tech Jobs & Startup Jobs in Des Moines, IA

Lead revenue accounting for a SaaS-like business: interpret contracts under ASC 606, manage month-end revenue close, own order-to-cash, prepare reports for monthly/quarterly statements, support audits, drive process improvements and automation, manage and mentor a small distributed billing/accounting team, and collaborate cross-functionally to ensure accurate revenue recognition and invoicing.

Lead end-to-end AI agent deployments: scope customer workflows, design and configure agent workflows, define integrations, coordinate engineering, monitor performance, and drive optimization and knowledge capture.

Lead and grow a payments engineering team responsible for payment platforms, integrations, tokenization, fraud signals, and reconciliation. Own delivery, production stability, on-call, PCI DSS compliance, vendor relationships, budget, and cross-functional coordination. Drive reliability, incident response, roadmap execution, and measurable improvements in transaction success, latency, and error budgets.

Lead design, build, and deploy Graph+GenAI solutions combining graph databases and LLMs. Act as trusted advisor to customers, architect scalable systems, write production code, integrate with orchestration and cloud platforms, optimize performance, and provide training, enablement, and product-feedback to stakeholders. Travel up to 50% to engage customers.

As a Technical Account Manager, you'll build strong customer relationships, translating business goals into technical strategies and ensuring success with Docebo's AI-powered learning platform.

Lead and build a best-in-class FP&A function for a high-growth managed services company. Drive budgeting, forecasting, driver-based modeling, variance analysis, and performance tracking. Partner with Sales, Delivery, and Marketing on pipeline, pricing, and margin optimization. Improve FP&A systems, automation, and analytics, prepare Board and investor materials, support M&A and due diligence, and scale a high-performing team while partnering with Controllership for accurate reporting.

Build and maintain scalable monitoring solutions and dashboards to track production, campaign, and operational data. Analyze large-scale datasets to detect anomalies, perform root-cause investigations with Engineering and Production Operations, and deliver actionable insights to improve platform reliability and operational efficiency.

Design, build, and maintain AI platform infrastructure and services. Implement scalable backend systems, REST APIs, CI/CD, observability, automated testing, and cloud-native streaming. Collaborate across teams, apply TDD, and use generative AI tools to accelerate development.

Lead Salesforce Product-to-Cash architecture, coach engineers, design HLD/LLD and roadmaps, govern integrations and billing systems, build POCs, apply AI-first solutions, and ensure scalable, secure Revenue Cloud/CPQ implementations across quoting, billing, invoicing, and revenue processes.

Product Manager for Data Platform owning roadmap and backlog to operationalize datasets, ensure trusted, well-modeled data, collaborate with engineering and product teams, run discovery with domain experts, enable data cataloging and governance, monitor data health and adoption, and drive cross-team alignment.

The Senior Product Manager will oversee product development from ideation to delivery, manage product backlogs, and collaborate with various teams to understand and solve customer needs while driving product innovation in the healthcare sector.

Provide practical, production-focused mentorship to managers and executives in business-facing AI programs: guide project work, clarify generative and agentic AI concepts, discuss deployment trade-offs, and share strategies for evaluation, governance, and scaling AI in organizations.

Provide part-time technical mentorship to learners in the Data Product Manager track: answer forum questions, host weekly live sessions, escalate issues, and guide students on data foundations, product KPIs, experiment design, data pipelines, modeling, visualization, and product frameworks.