Top Tech Jobs & Startup Jobs

Build and lead AssemblyAI’s digital-native sales organization, scaling Account Executives and front-line managers. Own revenue growth, hiring, org design, territories, quotas, compensation, forecasting, pipeline generation, and sales operating cadence. Partner with engineering, research, marketing, and customer-facing technical teams to convert product evaluations into production usage. The role requires technical credibility with APIs and AI infrastructure, experience scaling sales teams, strong recruiting ability, and frequent travel.

Productionize AI research into robust customer-facing APIs and services. Design, launch, and iterate model capabilities; scale inference infrastructure for high-volume traffic; partner with researchers and applied engineers to convert prototypes into reliable, low-latency products; and contribute to backend services, SDKs, inference systems, and internal tooling while incorporating customer feedback.

Design and ship customer-facing APIs exposing AI model capabilities, scale inference infrastructure, and productionize research techniques for reliable, low-latency production traffic. Collaborate with researchers, applied engineers, and customers to improve products and research direction. Contribute across backend services, inference infrastructure, SDKs, and internal tooling.

Build and scale customer-facing APIs and inference infrastructure for AI model capabilities. Productionize research prototypes into reliable, low-latency services, collaborate with researchers and applied engineers, support production traffic, and contribute to backend services, SDKs, and internal tooling. Engage with customers to inform product design and research direction.

Build and scale production inference infrastructure and customer-facing APIs for AI model capabilities. Partner with research and applied engineering teams to productionize prototypes into reliable, low-latency, well-documented services. Work with customers to inform product and research direction, while contributing across backend services, inference systems, SDKs, and internal tooling.

Develop and optimize large-scale deep learning training, data processing, and production inference systems. Maintain JAX and TPU training infrastructure, improve data quality and evaluation, translate research prototypes into production, optimize speech and language model inference, and resolve performance bottlenecks from kernels through system architecture. Collaborate across research, infrastructure, and production engineering while measuring impact and improving experimental velocity.

Build and scale production inference systems and customer-facing APIs for AssemblyAI’s voice AI models. Responsibilities include productionizing research prototypes, improving latency and reliability, supporting high-volume inference traffic, developing backend services and SDKs, and collaborating with researchers, applied engineers, customers, and product teams.

Build and scale production inference infrastructure and customer-facing APIs for AssemblyAI’s voice AI models. Partner with researchers and applied engineers to productionize model capabilities, transforming prototypes into reliable, low-latency, well-documented products. Contribute across backend services, SDKs, inference systems, and internal tooling while incorporating customer feedback into product and research direction.

Own AssemblyAI’s go-to-market technology stack, including Salesforce, enrichment, outbound automation, routing, scoring, and AI agents. Build production automations, integrations, internal tools, and AI workflows for prospecting, research, personalization, and lead scoring. Convert product usage data into actionable sales signals, automate account targeting, maintain clean funnel data, and partner with Sales and Marketing leadership to improve pipeline and revenue operations.

Serves as the primary legal partner to enterprise sales and owner of the commercial contracting lifecycle. Drafts and negotiates MSAs, DPAs, BAAs, and related agreements; advises on privacy, data protection, AI contract issues, intellectual property, model training, and data governance. Balances legal risk with deal velocity, manages high contract volume, and independently drives agreements from initiation through execution in a fast-paced startup environment.