Top Tech Jobs & Startup Jobs

Manage relationships with B2B and SMB retirement plan sponsors, handling inquiries, resolving complex issues, proactively retaining at-risk accounts, and developing customized save strategies. Collaborate with Sales, Product, Engineering, and Operations; document client interactions; maintain CRM records; and translate customer feedback into product insights. Use AI tools to improve case summaries, communications, trend identification, and resolution speed while supporting customer satisfaction and business outcomes.

Build and manage relationships with accounting firms and financial advisors, acquire and onboard new partners, drive client adoption, and grow partner business through consultative, value-based sales. Collaborate with Marketing, Product, and Customer Success to improve partner experiences. Future Account Executive and Account Manager opportunities will support Gusto’s partner ecosystem and may span multiple levels.

Own paid social strategy and execution across Meta, LinkedIn, Reddit, Quora, and TikTok, managing multimillion-dollar budgets and full-funnel campaigns. Lead creative testing, attribution, forecasting, and new-channel experimentation while driving pipeline and revenue outcomes. Develop AI-powered marketing workflows, partner with web, brand, sales, engineering, and communications teams, and ensure reliable tracking and measurement.

Workforce Management Analyst responsible for multi-department scheduling, intraday staffing decisions, queue and skill routing, performance analysis, dashboards, and WFM automation. The role partners with operations leaders and vendors, administers WFM and routing tools, responds to real-time alerts through PagerDuty, and drives actionable insights and staffing improvements. AI fluency, scripting, analytics, and contact center WFM expertise are central to the position.

Leads Gusto’s Risk & Money Services organization, overseeing fraud and payment risk, BSA/AML operational response, Reg E disputes, collections, and consumer money products. Builds governance, controls, SLAs, metrics, audit readiness, and scalable operating procedures while partnering with Product, Engineering, Compliance, Legal, sponsor banks, regulators, and auditors. Owns high-stakes financial decisions, customer experience, regulatory posture, team development, and AI-enabled transformation across Gusto’s financial services portfolio.

As a Senior Data Scientist, the role involves leveraging data analysis, experimentation, and statistical methods to influence business decisions and enhance Gusto's product performance, while mentoring team members.

Design, build, test, and scale Gusto’s payments infrastructure and platform. Make architectural decisions focused on fault tolerance, scalability, and modularity; modernize Ruby/Rails and TypeScript/React systems; collaborate across engineering, product, design, data science, and operations; deliver software supporting millions of businesses; and mentor fellow engineers.

Own the full sales cycle for Gusto’s PEO offering, from prospecting and discovery through demos, complex stakeholder navigation, and closing. Sell to net-new prospects and existing payroll customers, build broker and accountant referral channels, manage Salesforce pipeline and forecasting, and serve as a PEO subject matter expert. Leverage AI in daily sales workflows, collaborate cross-functionally, and help build the company’s founding PEO sales motion.

Lead go-to-market strategy and experimentation for new products, offers, and market motions. Develop segmentation, positioning, pricing, and cross-product narratives; synthesize market and customer insights; coordinate Product, Sales, Growth, Marketing, and Customer Experience teams; establish processes for ambiguous initiatives; define success metrics; and optimize performance through iterative testing. The role focuses on proving product-market fit before handing successful motions to established product marketing teams.

Build and scale Gusto's ML/AI platform: design MLOps solutions, automated pipelines, model development frameworks, deployment, monitoring, CI/CD, and observability; collaborate with ML engineers and apply AI tools and best practices to production ML systems.