Top Tech Jobs & Startup Jobs

Sell Instructure’s education technology solutions to K-12 school districts across Texas. Responsibilities include generating new business, expanding existing accounts, conducting needs analysis, developing proposals, guiding purchasing processes, forecasting sales, maintaining stakeholder relationships, achieving quotas, and recording account information in Salesforce. The role requires enterprise SaaS sales experience, consultative selling skills, and travel up to 50%.

Own technical accounting for complex transactions, including M&A, debt, equity, and evolving accounting standards. Lead GAAP financial reporting, audited financial statements, footnotes, debt covenant packages, and external audits. Research and document accounting conclusions, maintain strong SOX controls, collaborate with cross-functional teams, and oversee the Equity function. Drive automation and process improvements for financial reporting while providing executive-level guidance and managing the Equity Manager.

Manage multiple software implementations across Canada, serving as a trusted customer advisor and coordinating scope, objectives, technical requirements, project plans, milestones, risks, and delivery. Collaborate with customer success and engineering teams on XML overlays and guide customers through SSO, API, and XML integrations. Maintain Salesforce records, manage expectations, and deliver implementations in English and Canadian French.

Supports global Sales Operations through SQL reporting, pipeline and bookings analysis, forecasting insights, CRM data quality monitoring, territory and quota planning, capacity modeling, and leadership-ready recommendations. Partners with Sales, Finance, and Revenue Operations teams to standardize metrics, automate recurring reports, and support annual planning across regions and business units.

Technical leader responsible for architecting, building, and scaling the developer portal and PaaS. Drive architectural direction, write and review code, mentor engineering teams, collaborate with SRE and stakeholders, evaluate new technologies, troubleshoot complex issues, and improve engineering processes and platform reliability.

Provides technical customer support through troubleshooting, resolution planning, integration assistance, template modification, log monitoring, software testing, documentation, and issue escalation. Collaborates with development and global support teams, identifies process and product improvements, uses AI to optimize workflows, and handles customer and internal technical requests. The role is primarily remote, with occasional out-of-hours meetings and potential in-person office visits once or twice annually.

Lead forecasting and reporting for revenue, ARR, and bookings; build models and KPIs; run variance and ad-hoc analyses; write SQL against Snowflake; partner with sales ops and systems teams; support annual planning; improve FP&A processes and mentor juniors.

Generate qualified pipeline for higher education accounts through inbound lead qualification and outbound prospecting. Conduct personalized outreach via email, phone, and social channels; run discovery conversations; identify customer needs; and connect prospects with relevant solutions. Partner with Sales Representatives and Customer Success Managers on territory strategy, account prioritization, follow-up, and handoffs. Maintain accurate CRM records, prioritize opportunities using buyer intent and account signals, and continuously improve conversion through coaching and data-driven experimentation.

Manage strategic higher education accounts by developing success plans, leading executive business reviews, monitoring customer health, driving product adoption, and supporting retention and expansion. Use data and generative AI to identify risks, improve workflows, and strengthen customer engagement. Collaborate with Product Management, Sales, Renewal Representatives, and leadership while maintaining CRM records and managing a substantial SaaS portfolio.

Design and own learner models powering mastery and progression features. Build datasets, training and scoring pipelines, evaluation strategies, testing, versioning, and production monitoring for models handling sparse, noisy, evolving behavioral data. Partner with learning scientists, product, and infrastructure teams to define targets, assess calibration, uncertainty, fairness, stability, and interpretability, and clearly communicate model behavior and limitations.