Top Tech Jobs & Startup Jobs in NYC, NY

Own positioning, messaging, competitive intelligence, sales enablement, analyst relations, and go-to-market launches for Nadia, Valence’s enterprise AI coaching platform. Partner with sales, product, and executive leadership to sharpen enterprise messaging, improve deal execution, and build scalable marketing systems. The role requires translating complex AI products into compelling materials for CHROs and senior enterprise buyers while establishing the company’s first dedicated product marketing function.

Owns full-cycle recruiting across GTM and technical roles, partnering with leadership on role definition, hiring strategy, interview design, talent calibration, sourcing, candidate experience, and closing. The Lead Recruiter will build proactive pipelines, use funnel data and market intelligence to guide decisions, improve recruiting systems, influence senior stakeholders, and help shape employer brand and compensation practices in a high-growth AI company.

Lead application security for an AI-native enterprise coaching platform: review code and architecture, threat model, perform manual pentests, build security tooling, advise DevOps on infrastructure security, support incident response and SOC processes, and handle client-facing security needs.

Manage and grow strategic enterprise partnerships, lead consultative deployment of Valence's generative AI coaching platform, drive revenue/usage/expansion, embed as a programmatic partner to deliver measurable value, own renewals and contracting, influence product roadmap, and partner with Sales and Operations to ensure successful large-scale deployments.

Drive high-priority, cross-functional initiatives to scale the company: diagnose problems, create project plans, build decision tools, support sales/marketing/product, manage pilots, and partner with leadership on metrics and quarterly planning.

Build and operate Valence's shared platform primitives (auth, routing, LLM gateway, deployment, observability, SLOs) to enable safe, scalable, and compliant delivery of AI-first products. Implement CI/CD gates, progressive delivery, rollback automation, security guardrails, region-aware routing, and developer-facing templates and tooling.

Design, build, and productionize LLM-based conversational and AI systems for enterprise coaching. Integrate structured and unstructured data, prototype end-to-end services, improve model behavior and observability, and collaborate with product and engineering to deploy scalable, reliable AI-driven coaching workflows.

Design and build full-stack features for an LLM-powered coaching platform: architect backend services and APIs, integrate models, craft responsive front-end experiences, ensure enterprise-scale performance and security, drive CI/CD and observability, debug across the stack, and mentor engineers while collaborating with product and design.

Own the operational system for enterprise product launches: drive direct client activation, resolve IT/security blockers, build repeatable launch playbooks, track adoption metrics, synthesize client feedback into product influence, and coordinate cross-functional release and incident processes.

Design end-to-end features across an AI-native enterprise coaching product, own feature delivery, maintain the design system, collaborate tightly with product and engineering, write product copy/micro-interactions, and explore intuitive AI UX.