Jobs at Salesloft

Manage a B2B SaaS customer portfolio to drive retention, adoption, expansion, and advocacy. Use product usage data, AI-generated health signals, and engagement scoring to prioritize proactive account action. Lead executive business reviews, demonstrate ROI, support onboarding and enablement, identify expansion opportunities with Account Management, and communicate customer feedback to Product and Engineering.

Own full-cycle enterprise sales, from prospecting and qualification through negotiation and close, focused on acquiring new logos. Build relationships with senior and C-level stakeholders, execute account and territory plans, lead consultative sales conversations, use AI-powered sales intelligence to manage pipeline and forecasts, and coordinate Sales Engineering, Customer Success, and Marketing resources. The role requires proven B2B SaaS hunting and closing experience, enterprise deal expertise, quota attainment, and familiarity with structured sales methodologies.

Own strategy, architecture, configuration, integrations, and optimization for G&A and Finance business systems. Serve as product owner by defining roadmaps, prioritizing features, managing system lifecycles, evaluating solutions, and delivering AI use cases. Partner with business leaders, improve processes, document system flows, establish configuration standards, and drive adoption, reliability, and compliance across the enterprise systems environment.

Own end-to-end learning and enablement programs, including manager development, onboarding, workshops, People Team playbooks, and learning architecture. Partner with People Business Partners to address talent gaps, operate the LMS and content library, apply AI to learning workflows, and measure program impact. The role requires strategic business partnership, instructional design, hands-on program delivery, stakeholder influence, and continuous improvement of workforce learning.

Serves as a strategic people advisor to business leaders, owning workforce planning, organizational design, succession planning, change management, talent calibration, employee engagement, and complex employee relations. Uses HRIS and workforce data to recommend actions that improve engagement and retention while advising executives, directors, and managers. Partners with Talent Acquisition, Total Rewards, Benefits, Legal, and shared services teams.

Serves as the strategic people advisor to Customer organization leaders, owning workforce planning, organizational design, succession planning, employee relations, performance management, talent calibration, engagement, organizational change, and people strategy. Advises executives and managers, analyzes workforce data, leads complex investigations, develops scalable people programs, uses AI responsibly, and mentors HR partners.

Own commercial customer accounts across the full sales lifecycle, including renewals, upsells, cross-sells, prospecting, forecasting, retention, and expansion. Build executive relationships, conduct software demonstrations, identify growth opportunities, manage churn risks, and exceed revenue quotas. Collaborate with Customer Success, Product, Support, and Sales Engineering teams to resolve issues and close opportunities within the SMB segment.

The Senior Data Analyst will drive performance monitoring and decision-making through actionable insights, complex data analysis, and visualization. Responsibilities include KPI identification, dashboard creation, and training for data-savvy users.

Build and maintain scalable data pipelines, transformation layers, and data services supporting internal reporting, business intelligence, analytics, and machine learning. Collaborate with data scientists and analysts to deploy models and solutions, integrate third-party data, optimize Snowflake warehouses, test and review code, and deliver production-ready infrastructure.

Manage employee relations, investigations, leave processes, offboarding, exit interviews, workforce trend analysis, policy development, compliance projects, and internal communications. Partner with managers to deliver consistent employee support, improve engagement and retention, and maintain a high-quality employee experience across the organization.

Lead the design, development, scaling, and operation of backend services supporting millions of workflows daily. Architect AI-based revenue forecasting solutions, resolve complex production issues, improve reliability and performance, build reusable data integrations and developer tooling, contribute to technical architecture, and mentor engineers. The role requires expertise in Java or Go, distributed systems, cloud platforms, databases, observability, testing, and enterprise-scale production software.

Own enterprise customer success by driving product adoption, retention, expansion, and measurable ROI. Build mutual success plans, conduct executive QBRs, analyze customer data, provide strategic sales-engagement guidance, and manage stakeholder relationships. Lead customer meetings, webinars, trainings, and difficult conversations while partnering with internal sales, finance, marketing, and leadership teams. The role also supports onboarding and mentoring newer customer success managers.

Manage a portfolio of SaaS customers by driving product adoption, retention, expansion, and satisfaction. Build mutual success plans, conduct QBRs, analyze customer data, demonstrate ROI, provide sales engagement guidance, and lead executive-level meetings, webinars, and trainings. The role requires cross-functional collaboration, stakeholder management, strong communication, technical fluency, and strategic customer relationship ownership.

Design and implement solutions to improve availability, resiliency, and operational maturity of cloud services. Define and implement SLIs/SLOs, improve failure detection and isolation, participate in incident response and retrospectives, build/manage critical third-party services, influence system design, and optimize systems for fault tolerance, disaster recovery, and efficiency while mentoring peers.

Support and scale cloud-based RDBMS and NoSQL systems, build automation/IaC for deployments, manage backups and HA, monitor and troubleshoot performance, collaborate on schema changes, and enforce data integrity and security standards to ensure reliable 24/7 operation.

Conduct machine learning research, develop AI and ML product feature prototypes, and solve business problems using structured and unstructured data. Collaborate with product, engineering, sales, and customer success teams to define data science initiatives. Apply statistical methods, NLP, classic machine learning, and agentic AI. Manage complex projects, translate research into actionable insights, and communicate technical concepts to stakeholders.

Own AI and machine learning research projects that improve sales productivity. Apply agentic systems, NLP, and machine learning; design experiments; develop prototypes and production-ready models; collaborate with product, design, and engineering; influence the AI roadmap; and mentor junior researchers.

The Principal Software Engineer will lead the design and build-out of an AI Context Layer, ensuring high-quality data for AI systems, while managing access control and developer interfaces, and leading cross-team projects.

The role involves managing a team of engineers, providing mentorship, conducting performance reviews, handling customer escalations, and leading development initiatives to enhance the product and support sales engagement strategies.

SalesLoft invites individuals interested in joining their company to submit their resumes for future opportunities, emphasizing a supportive culture and growth potential.