Top Tech Jobs & Startup Jobs in NYC, NY

The Engineering Manager will lead a team in Applied AI, focusing on building scalable systems, driving evaluations to improve model performance, and managing engineering talent.

The Enterprise AI Associate will engage with customers, support AI solution deployment, and translate feedback into structured plans while collaborating with engineering teams and refining marketing strategies.

The Fullstack Software Engineer will develop and manage the Studio platform's frontend and backend, ensuring reliable data workflows and user-friendly interfaces. Responsibilities include leading engineering best practices, collaborating on technical solutions, and shipping impactful features for AI data generation and delivery.

Design and operate cloud infrastructure security for multi-tenant environments: architect multi-account AWS isolation, harden Kubernetes, deploy CSPM, enforce IaC guardrails, implement least-privilege IAM across platforms, and build incident response and logging pipelines for enterprise customers.

As a Software Engineer, Applied AI, you'll architect and implement integrations and scalable solutions for enterprise clients, focusing on technical requirements and business goals.

Build systems for Mercor's hiring engine, including pipelines for indexing, sourcing, scoring, and conversion. Work with ML and backend technologies.

Lead a customer-facing applied AI engineering team to deliver production-grade, cloud-native AI systems. Translate customer workflows into scalable agentic solutions, oversee deployments, evaluation and continual-learning loops, hire and mentor engineers, remove blockers, and coordinate with Sales, Product, Research, and Platform teams to ensure reliable, scalable enterprise deployments and measurable commercial outcomes.

The Enterprise AI Lead will manage relationships with clients, develop commercial strategies, drive initiatives across teams, and present to executives, requiring strong communication and problem-solving skills.

Own end-to-end data delivery and operations for RL training environments: scope projects, manage distributed contributor teams, meet throughput and quality targets, partner with engineers to unblock pipelines, drive process improvements, and deliver high-pressure client requests on tight timelines.

Own full-cycle recruiting for Deeptune and adjacent teams: source through close, partner with hiring managers to define roles, build top-of-funnel, coach interviewers, operationalize hiring systems and metrics (Ashby), drive fast, high-quality hiring, and represent Mercor externally.