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Perform outbound prospecting to identify and qualify new business opportunities with Fortune 1000 executives and investment professionals. Use email, phone, and social outreach, research target accounts, handle discovery and objections, schedule meetings for Account Executives, log activity in CRM, and consistently achieve program KPIs.

The Account Executive will drive new business sales across Financial Services, manage the sales pipeline, conduct demos, and build relationships with clients, while exceeding revenue targets.

Lead product strategy and execution for AI-driven expert research: translate investor needs into AI workflows, define roadmap, run user research and experiments, collaborate with engineering/design, and drive launches while optimizing accuracy and reliability of LLM/ML outputs.

Provide first-line customer and product support for AlphaSense’s platform via email, chat, and calls. Troubleshoot, triage, and escalate issues; drive documentation and training; partner with Product, Engineering, and SRE on incidents and feature feedback; own knowledge base updates and beta feature testing.

Lead quality strategy for an AI-first platform: define testing standards, metrics, and automation; validate AI models and data pipelines; design API and UI tests; coach teams on shift-left quality and release gates; improve observability and performance practices to ensure scalable, data-driven quality outcomes.

Own and evolve AlphaSense's structured financial data taxonomy, define label conventions and governance, collaborate cross-functionally to implement scalable, production-ready data structures, ensure AI/LLM compatibility, document standards, resolve onboarding inconsistencies, and build repeatable taxonomy frameworks for future growth.

The Account Executive will focus on new business acquisition in the Financial Services market, managing end-to-end sales processes, and building strong client relationships to achieve sales targets.

Design, operate, and evolve CI/CD and delivery infrastructure for ~400 engineers. Build developer-facing tooling, champion progressive delivery (canaries, automated rollbacks), own end-to-end delivery from merge to production, improve pipeline reliability and speed, evolve the Internal Developer Portal, and embed AI-assisted workflows into the software development lifecycle.

Lead architecture and implementation to scale a large Kubernetes-native microservice platform into cell-based deployments. Decompose services, build shared libraries and configuration frameworks, enable private/isolated cloud deployments, land changes in product services, set architecture patterns, partner with Cloud Platform/SRE/DevEx, mentor senior engineers, and embed AI tooling into development workflows.

Design and own CI/CD and configuration management for a large-scale, multi-cluster Kubernetes fleet. Define GitOps-driven, declarative reference architectures and templated production environments. Implement progressive delivery (canary, automated rollback), improve pipeline reliability and speed, evolve the Internal Developer Portal, embed AI tooling into delivery workflows, and partner with Cloud, Security, and Compliance while mentoring senior engineers.