Jobs at ASAPP

Serve as the senior technical advisor for enterprise customers adopting conversational and agentic AI. Lead executive briefings, architecture discussions, and workshops; guide customers on AI strategy and platform adoption; shape reusable product capabilities; collaborate with Delivery, Research, Engineering, Product, and customer-facing teams; and represent ASAPP through public content, talks, and industry conversations.

Lead cloud, application, AI, and zero-trust security for an AWS-based microservices platform. Design security architecture, secure Kubernetes and CI/CD environments, build detection and monitoring pipelines, lead incident response and threat hunting, perform threat modeling, manage vulnerabilities, and protect LLM-powered systems. The role also involves customer-facing security deep-dives and technical leadership across engineering teams.

Manage ASAPP’s channel partnership motion, including recruiting and negotiating with strategic partners, developing channel plans, forecasting partner-sourced pipeline, and co-selling opportunities through close. Own partner onboarding, enablement, integrations, joint marketing, KPI tracking, and partner relationships. Collaborate with Sales, Product, Engineering, Finance, Marketing, and external technology partners, resellers, consultancies, and service providers to drive measurable revenue.

Own the strategy, roadmap, and outcomes for ASAPP’s Messaging Platform, Virtual Agent, communication channels, and AI Services. Lead product decisions across human-agent productivity, automated conversations, AI-assisted workflows, channel architecture, documentation, metrics, and telemetry. Partner directly with enterprise customers, engineering, design, sales, and customer success to prioritize investments, manage tradeoffs, and deliver measurable improvements in customer experience, agent efficiency, quality, and compliance.

Analyze large-scale Generative AI deployments and conversational data to identify customer growth opportunities. Develop performance insights, forecasts, and impact analyses; support Customer Success and Strategy teams with client and stakeholder requests; and communicate recommendations through compelling presentations. Collaborate cross-functionally with Customer Success, Engineering, and Product teams to shape account strategies and improve customer experience outcomes.

Lead ASAPP’s product strategy, portfolio, and product organization as it scales enterprise AI products. Define product direction, convert AI research into reliable commercial offerings, identify repeatable customer needs, and oversee products from incubation through adoption and expansion. Partner closely with customers, engineering, research, sales, delivery, and design while setting standards for AI quality, safety, reliability, metrics, and operational execution. Recruit and develop exceptional product and design leaders and guide enterprise positioning, packaging, and deployment strategy.

Lead development of an evaluation platform for agentic AI and LLM systems. Design benchmarking, human review, LLM-as-judge, monitoring, annotation, dataset versioning, and data quality workflows. Own technical architecture, production infrastructure, stakeholder reporting, and platform health while partnering with research, product, and platform teams. Mentor engineers and support scalable AI experimentation and deployment.

Drive mid-market SaaS revenue by prospecting, managing the full sales cycle, conducting product demos, negotiating contracts, closing net-new business, and maintaining CRM records. The role requires building pipelines, researching prospects, nurturing executive relationships, and leveraging internal resources to meet sales targets.

Manage customer-facing software and AI delivery projects from initiation through closure. Build project plans, coordinate technical and business teams, communicate status and risks to enterprise customers and executives, support escalations, and improve PMO practices. The role also involves mentoring team members, evaluating AI use cases and data readiness, tracking AI-specific risks, and setting realistic expectations for conversational AI and generative AI deployments.

Own the customer-facing data layer: roadmap for dashboards and analytics, data feeds/APIs, data strategy and schema design, customer discovery for KPIs, partner with engineering/data science, and maintain trust in data quality and availability to demonstrate GA value and ROI.