Top Remote Senior Level Jobs in Pittsburgh, PA

Build and deploy production-grade agentic workflows for enterprise customers using Webflow APIs, CMS, AI capabilities, and external integrations. Design safeguards, observability, rollback paths, and permission boundaries; support live web properties at scale; collaborate with sales and engineering on complex deployments; and convert customer implementation learnings into reusable architecture blueprints and platform improvements.

Own and scale strategic relationships with systems integrators and enterprise audit firms. Drive partner-sourced revenue, co-selling, partner enablement, onboarding, forecasting, and executive engagement. Advocate for Drata products, improve audit experiences, coordinate with Sales, Marketing, Product, Engineering, and Customer Success, and help shape the broader alliance ecosystem strategy.

The Enterprise Account Executive will drive enterprise sales of the Qualtrics Experience Management platform, engage with Fortune 100/500 clients, and consistently meet sales quotas while managing relationships.

Leads the development and ownership of Cedar’s production machine learning personalization engine. Responsibilities include ML modeling, MLOps, feature pipelines, deployment, inference, monitoring, feedback-loop optimization, compliance and fairness guardrails, technical leadership, code reviews, cross-functional collaboration, and management of ML engineers. The role requires hands-on contributions to scalable ML systems serving millions of healthcare transactions while guiding roadmap execution and model improvement.

Own the full technology partner lifecycle, from qualification and commercial agreement through integration, activation, joint go-to-market, and royalty revenue generation. Manage a partner territory, forecast performance, conduct QBRs, coordinate with Product, Engineering, and Marketing, and build scalable onboarding and activation playbooks. The role requires enterprise SaaS partner management, commercial negotiation, partner economics expertise, technical fluency, and experience driving integrations and marketplace distribution.

Leads enterprise sales and strategic customer relationships for RigUp’s downstream energy solutions. Responsibilities include prospecting, pipeline management, proposals, negotiations, onboarding, account growth, market development, and cross-functional coordination with Operations, Product, Marketing, and Leadership. The role requires deep downstream oil and gas expertise, C-suite relationship development, complex RFP ownership, frequent client travel, AI-enabled sales workflows, and mentorship of account team members.

Leads Learning, Content, and Quality teams within Shared Services. Owns the strategic vision, operating models, onboarding curriculum, train-the-trainer programs, knowledge bases, quality processes, performance metrics, and AI enablement strategy. The role develops high-performing teams, reduces frontline ramp time and turnover, creates closed-loop feedback systems, and aligns training outcomes with operational KPIs while scaling support operations.

Drives revenue growth by prospecting for new compliance customers, expanding existing accounts, and selling Skillsoft’s legal, ethics, safety, and OSHA compliance solutions. Responsibilities include outbound prospecting, pipeline development, consultative solution selling, executive engagement, cross-functional collaboration, upselling, negotiation, presentations, and deal closure. The role requires managing whitespace opportunities, reporting pipeline health, and consistently exceeding sales targets in a remote, matrixed environment.

Build and lead GC AI’s revenue operations function from the ground up. Develop go-to-market processes, hire and manage a high-performing team, select and implement operational technology, align Sales, Marketing, Product, Customer Success, and Partnerships, and optimize pipeline, forecasting, retention, deal velocity, win rates, and revenue performance through data-driven KPIs.

Build AI-augmented BI dashboards, semantic layers, and AI-ready metadata. Use AI-assisted tools to accelerate SQL and dashboard development, productionize ML outputs into BI, enforce data quality and governance, and present insights to business stakeholders including C-suite.