Top Tech Jobs & Startup Jobs in NYC, NY

Coordinate interview scheduling, feedback, next steps, onsite logistics, executive interviews, and candidate communications across the company. The role ensures a high-quality candidate experience, manages overlapping interview processes, maintains hiring momentum, and identifies opportunities to improve recruiting operations and logistics.

Leads quantitative and qualitative Medicaid policy research from project scoping through dissemination. Oversees data acquisition and analysis, monitors state and federal policy changes, develops briefs and presentations, conducts stakeholder interviews, supervises research staff, manages external collaborators, and translates findings into actionable recommendations for policymakers, providers, advocates, and the public.

Design, implement, and maintain production-oriented NLP and LLM models; build data pipelines and HPC analyses; integrate ML solutions with clinical research tools; ensure data quality, privacy compliance, and collaborate across multidisciplinary teams.

Handles incoming owner-relations calls involving revenue, land, division orders, joint interest billing, accounts receivable, and accounts payable. Logs and follows up on inquiries, resolves customer issues, builds client trust, manages difficult interactions professionally, and provides accurate, timely responses by phone and email. The role also involves cross-training and collaboration to improve customer experience and business operations.

Supports people operations and workplace experience for the US team by coordinating hiring, onboarding, offboarding, employee engagement, office operations, events, vendors, inventory, hardware setup, and leadership support. The role serves as a central point of contact for candidates and employees, manages office and team logistics, and helps maintain a positive, organized, and well-equipped workplace.

Own client pilots for an agentic AI platform that reviews construction documents. Scope use cases, configure AI workflows, present results to reviewers, design solutions for product gaps, and translate client needs into product requirements. The role requires experience in architecture, structural, mechanical, or electrical engineering, owner/developer organizations, or AECO startups, along with frequent use of AI tools and workflow-building experience.

Sources, engages, interviews, evaluates, signs, and activates therapists across multiple markets. Manages provider onboarding and credentialing, maintains accurate pipeline data, diagnoses funnel performance, tests sourcing strategies, and collaborates with Operations, Clinical, Growth, Credentialing, and Provider Support teams to expand therapist supply.

Build and scale Credal’s secure AI platform as a founding full-stack engineer. Own stability, scalability, security, architecture, and product quality while syncing billions of customer records reliably. Develop across frontend, backend, cloud, and AI/ML systems; collaborate directly with customers and go-to-market teams; mentor engineers; and take end-to-end ownership of complex technical and product outcomes.

Build polished web and mobile interfaces for AI agents, including streaming output, real-time progress, citations, approvals, and data-dense research workflows. Own front-end architecture, performance, accessibility, testing, telemetry, and design systems. Develop supporting APIs, streaming endpoints, agent state and session services, MCP tools, and integrations. Collaborate with applied researchers, infrastructure engineers, designers, and product managers to deliver agentic capabilities end to end.

Lead enterprise data architecture across warehouses, data lakes, downstream applications, and AI workloads. Design data models, Medallion Architecture, ELT standards, semantic layers, APIs, access controls, and reusable datasets. Partner with business and BI teams to drive adoption, conduct architecture reviews, establish platform standards, and mentor data and analytics engineers. The role requires deep Snowflake, dbt, data modeling, pipeline, and semantic-layer expertise, with experience in AI data patterns and cloud infrastructure preferred.