Top Remote Senior Level Jobs in Wichita, KS

Build core experiences for bank administrators and customers by developing streamlined user flows, robust APIs, and third-party integrations. The role emphasizes clean, documented, tested code; system design; error handling; performance; domain-driven design; microservice architecture; and technical guidance through code reviews. Candidates will primarily work with front-end technologies while contributing to backend services in an agile Scrum environment.

Drive new business and expansion within large enterprise accounts: source and close net-new logos, map complex organizations, build executive sponsors and champions, run data-driven POCs and ROI analyses, collaborate with internal teams, and consistently hit ARR targets through repeatable, metric-based sales strategies.

Plans and oversees multimedia editorial projects for high school educational products, coordinating authors, vendors, freelancers, and internal teams. Manages schedules, budgets, workflows, content quality, and stakeholder communications. Evaluates user needs and platform functionality, supports marketing and sales materials, and improves editorial processes through AI and automation. The role also recruits and manages external contributors, assesses project status, and promotes products through conferences and presentations.

Owns expansion and modernization across complex enterprise accounts by developing account strategies, creating demand, leading consultative discovery, shaping technology solutions, negotiating commercial terms, and closing opportunities. Coordinates cross-functional pursuit teams, manages forecasts and CRM records, builds executive relationships, develops business cases, and uses AI-enabled sales tools to improve opportunity management. Requires strong expertise in enterprise technology sales, customer business drivers, and multi-stakeholder negotiations.

Leads BILL’s AI and platform product partnership strategy, managing relationships with frontier AI companies and software vendors. Sources and structures deals, negotiates agreements, drives integrations and connector approvals, develops go-to-market and monetization plans, and coordinates execution across product, engineering, sales, marketing, finance, and executive leadership. Builds partnership roadmaps, evaluates opportunities, models deal economics, and creates scalable processes for a growing ecosystem.

Own end-to-end financial data analysis, including SQL and dbt data modeling, Looker dashboard development, data quality validation, reconciliation, and stakeholder-facing insights. Partner with Finance and Payments to support reporting, planning, revenue analysis, cost insights, and transaction-level analytics. Translate ambiguous business needs into reliable technical solutions while improving documentation, QA, modeling, and data architecture practices.

Lead full-cycle recruiting for multiple concurrent searches across go-to-market, technical, marketing, legal, and corporate functions. Develop sourcing strategies, engage passive candidates, screen applicants, partner with hiring managers, maintain pipelines and ATS records, coordinate interviews, provide market and pipeline updates, and support candidates through accepted offers. The recruiter must operate independently, manage shifting priorities, and deliver qualified pipelines and hires during the approximately 90-day engagement.

Leads the development, standardization, delivery, and continuous improvement of sUAS training programs. Oversees instructional designers and curriculum developers, establishes training architecture and standards, evaluates instructors, manages curriculum lifecycle, supports product training launches, conducts audits and validations, and delivers technical and operational instruction across classroom, manufacturing, flight-line, customer, and field environments.

Lead development and deployment of predictive and ML models for credit risk, collections, and operations. Mentor data scientists, promote MLOps and modern tools, present insights to stakeholders, and drive experimentation with techniques such as causal inference and GenAI.

Build scalable data foundations, analytics tooling, analysis pipelines, and trusted datasets for product and data science teams. Establish instrumentation and experimentation standards, improve data quality and discoverability, document metrics and workflows, and collaborate across Product, Engineering, Data Science, Data Engineering, and Business Intelligence. Use AI to accelerate engineering while validating outputs through testing, data validation, source-checking, and peer review.