AssemblyAI

• Own a book of AI-native startup accounts, leading potential customers across the full sales cycle from prospecting through initial production rollout • Generate pipeline through proactive, creative outbound - including personalized outreach, conferences, exclusive events, and finding warm introductions • Craft outbound communications that deliver real value to prospects - custom benchmarks, competitive insights, use-case-specific demos that earn replies • Develop authentic champions within target accounts who advocate for AssemblyAI internally and help shepherd deals to close • Engage multiple leadership stakeholders in parallel - CTO, CPO, VP Engineering, VP Product, VP of AI, and other technical decision-makers - to build consensus and de-risk deals • Position AssemblyAI’s value and pricing against alternatives with clear, quantitative and qualitative differentiation • Drive urgency through business value at every touchpoint, keeping deals moving forward with intent • Quarterback complex, multi-threaded deals - bringing insights, perspective, and momentum to every customer interaction • Partner closely with Customer and Technology Teams to represent the voice of the AI-native customer and shape go-to-market strategy

• Conduct threat modeling and security design reviews for new features • Perform secure code reviews and provide actionable feedback • Deploy and maintain security tooling across the development lifecycle • Partner with platform engineering on infrastructure and environment security • Contribute to incident response for security events • Drive vulnerability triage and prioritization across teams • Partner with sales and legal responding to customer and vendor questionnaires • Support compliance audit cycles by gathering evidence and documenting controls • Monitor and respond to alerts from endpoint, cloud, and application security tools • Maintain and improve security runbooks and process documentation

• Own a portfolio of in-flight leads across AssemblyAI’s product lines, driving them from first API call to consistent production usage against a quarterly new-customer goal. • Reach out proactively the moment a developer’s usage ramps, diagnosing what’s blocking them from scaling and removing it before they go quiet. • Read unfamiliar customer codebases quickly and ship working patches alongside their engineers, debugging real-time audio, WebSocket, and latency issues directly in their service. • Tune model configurations for each use case—end-of-turn detection, keyterms, language coverage, async vs. real-time—and translate the tradeoffs to technical and non-technical stakeholders alike. • Run discovery and architecture conversations about customer use cases, knowing when to push back and when to lean in. • Steward technical wins through to commercial close: DPAs, MSAs, security reviews, stakeholder mapping, and multi-threading the buying team. • Hand off graduated accounts cleanly with the context and written history required for a smooth transition. • Aggregate lead feedback into structured signals for Product and Engineering, making sure the self-serve experience improves measurably because of the patterns you surface. • Build internal tooling—agents, dashboard, AI workflows—that help the team operate ahead of the wave as lead volume grows.

• Design and ship customer-facing APIs • Partner with researchers to productionize new techniques • Work with Applied teams to understand user interactions • Contribute across the stack

• Serve as the primary point of contact for customers, ensuring their needs are met throughout their journey with AssemblyAI. • Evaluate customer use cases and proactively identify opportunities to integrate voice AI into their product roadmaps. • Manage a portfolio of technical customers, primarily communicating asynchronously and ensuring timely, high-quality support. • Lead commercial and project meetings, focused on demonstrating the value of our voice AI capabilities. • Drive growth in customer usage of the API across varying product offerings and end customer use cases. • Build strong connections with our customers to ensure their long-term success with our platform. • Act as a thought leader and customer advocate, providing insights and feedback to drive the future direction of our product roadmap.

• Own a book of enterprise accounts, leading potential customers across the full sales cycle from prospecting through initial production rollout • Generate pipeline through proactive, creative outbound - including personalized outreach, conferences, exclusive events, and finding warm introductions • Craft outbound communications that deliver real value to prospects - custom benchmarks, competitive insights, use-case-specific demos that earn replies • Develop authentic champions within target accounts who advocate for AssemblyAI internally and help shepherd deals to close • Engage multiple leadership stakeholders in parallel - CTO, CPO, VP Engineering, VP Product, VP of AI, and other technical decision-makers - to build consensus and de-risk deals • Position AssemblyAI’s value and pricing against alternatives with clear, quantitative and qualitative differentiation • Drive urgency through business value at every touchpoint, keeping deals moving forward with intent • Quarterback complex, multi-threaded deals - bringing insights, perspective, and momentum to every customer interaction • Partner closely with Customer and Technology Teams to represent the enterprise voice of the customer and shape go-to-market strategy

• Serve as the first stop for any website question or idea — triaging, routing to the right partners, and owning follow-through • Create new solution, use case, and product pages end-to-end — owning the narrative and copy, partnering with brand and web on build and publish • Keep existing pages accurate and consistent as the product and positioning evolve • Write and update copy that reflects our infrastructure-first API positioning • Translate technical capabilities into crisp, compelling narratives that tie to business outcomes • Serve as an internal expert on our top use cases — voice agents, medical scribes, AI note takers, customer calls — including the buyers, competitors, and market dynamics in each • Develop executive-level positioning and strategic narratives for buyers in those target use cases, and translate them into decks, landing pages, and campaigns • Translate new product and feature launches into use-case-specific solutions campaigns • Spot emerging use cases and verticals based on customer feedback, signup trends, and market signals — and flag where we should lean in next • Build and maintain decks, one-pagers, battlecards, and messaging guides • Drive enablement programs that give the org a shared understanding of our target buyers and how to sell to them • Collaborate with lifecycle and demand gen on activation campaigns — email nurtures, onboarding flows, and personalized targeting based on signup behavior

• Be the first line of support AssemblyAI's customers. • Serve as the "product expert". • Wear multiple hats. • Be the liaison between the customer and our engineering teams. • Manage and contribute to our technical resources.

• Own model evaluation across accuracy, latency, and metrics • Build benchmarking pipelines • Design experiments to measure model impact • Manage evaluation datasets • Define real-world performance metrics • Summarize findings for leadership

• Design and implement tooling that enables researchers to quickly deploy and evaluate new models in production • Design, build, and maintain high-performance, cost-efficient inference pipelines, making architectural decisions about scaling, reliability, and cost trade-offs • Proactively identify and resolve infrastructure bottlenecks, proposing and scoping improvements to iteration speed and production reliability • Develop and maintain user-facing APIs that interact with our ML systems • Implement comprehensive observability solutions to monitor model performance and system health • Troubleshoot and lead resolution of complex production issues across distributed systems, driving root-cause analysis and implementing preventive measures • Set the direction for and continuously improve our MLOps practices, identifying the highest-impact opportunities to reduce friction between research and production. • Collaborate closely with research and engineering teams to align on technical direction, and help onboard and mentor engineers on ML infrastructure best practices.