Top Remote Jobs in Wichita, KS

Flexible, remote contract role supporting AI-moderated user research: build and refine discussion guides and screeners, manage participant recruitment and fielding, and assist Customer Experience with research execution. Requires strong qualitative/mixed-methods experience and familiarity with AI/unmoderated research platforms. ~20–40 hrs/week, 3-month minimum engagement.

Create and maintain technical knowledge articles, troubleshooting guides, runbooks, decision trees, and training materials to improve support case resolution. Partner with SMEs, analyze case trends, capture repeatable troubleshooting workflows, maintain content quality, and prioritize a backlog of enablement requests to enhance Support efficiency and escalation accuracy.

Senior, full-cycle recruiter responsible for sourcing and hiring Sales Account Executives across the Americas. Build proactive pipelines via LinkedIn Recruiter and sourcing tools, partner with sales leaders on hiring strategy and compensation, manage interview scorecards and process, deliver pipeline health updates, and negotiate offers to close high-quality, diverse candidates.

Build and scale a sales enablement function for a high-growth B2B SaaS company. Own onboarding, product enablement, launch readiness, and ongoing learning programs. Create sales plays, demo guides, certifications, and role-specific learning paths. Deploy AI and automation to make product knowledge discoverable and continuously updated. Partner across Product, Marketing, Sales, Partnerships, and Customer Success to drive seller productivity, reduce ramp time, and measure enablement impact through KPIs.

The Sales Engineer will support Account Executives by aligning Superhuman's solutions with educational institutions’ needs, delivering demos, conducting POCs, and engaging with technical stakeholders.

Lead and execute brand design across campaigns, events, and systems. Translate strategy into scalable visual systems, own end-to-end design delivery, maintain brand libraries and documentation, enable teams with templates and guidance, and collaborate with cross-functional and specialty teams for consistent brand application.

Lead the Pipeline team to own strategy and execution for MongoDB's end-to-end software delivery platform. Drive reliability, scalability, security, developer experience, CI/CD and release systems, telemetry, and organizational growth while partnering across engineering and product.

Lead teams focused on developer productivity and observability, build metrics and analytics infrastructure, and drive AI-enabled tooling to measurably improve the software development lifecycle. Partner with engineering and data stakeholders to define roadmaps, mentor engineers, and deliver measurable improvements in adoption, reliability, and developer experience.

Lead technical onboarding and solution architecture for enterprise wealth management clients. Translate client goals into platform designs, manage integrations (CRM, data warehouse, APIs), drive adoption, mentor delivery teams, influence product strategy, and ensure successful handoffs to Client Success.

Own and optimize the MarTech stack and marketing automation to drive lead generation, ABM, email, and paid acquisition. Manage HubSpot, Salesforce integrations, WordPress lead capture, Braze journeys, audience segmentation, testing, and reporting. Build dashboards, multi-touch attribution, and provide data-driven recommendations to improve pipeline, conversion rates, and ROI while partnering with Sales, Growth, and Client Success.

Own state-level product strategy and market performance for assigned regions. Manage state filings and DOI relationships, collaborate with Technology and Operations on launches, analyze KPIs and profitability drivers, present strategic recommendations, support external data and competitor intelligence, and relay field feedback to product teams to inform product changes and new development.

Design, build, and own scalable data pipelines and evaluation systems that power production AI features and internal analytics. Ensure data quality across ingestion, modeling, and reporting, collaborate with ML and analytics teams, deploy and monitor ML systems, and establish standards for data work and evaluation.