Top Tech Jobs & Startup Jobs in NYC, NY

Design and implement enterprise data and lakehouse architectures for client data, cloud, and AI transformation initiatives. The role requires hands-on expertise with Databricks, Azure, GCP, Spark/PySpark, SQL, Unity Catalog, governance, Terraform, and CI/CD. Responsibilities include client-facing solution architecture, clear communication, and delivery of scalable analytics solutions. Databricks Champion status is mandatory, while DPP experience is preferred. Immediate or 30-day-or-less availability is preferred.

Field-first outside sales role to acquire new accounts and grow territory across universities, dental, dermatology/aesthetics, and ASI/decorator channels. Own full sales cycle, build pipeline, execute in-person demos/fittings, enable distributor partners, maintain CRM hygiene, manage licensing/EDI/compliance, collaborate with marketing and operations, and deliver weekly activity and monthly forecasts. Frequent travel required.

Build and ship P-1 AI’s core product platform for Archie, an AI engineering agent. Own end-to-end features spanning architecture, backend, frontend, deployment, and reliability. Collaborate with AI researchers, forward-deployed engineers, founders, and customers to rapidly prototype, launch, and refine product concepts. Establish advanced AI-assisted development practices and continuously improve engineering workflows, product quality, and delivery speed.

Provide expert client support for mortgage loan registration and structuring, analyze AUS findings and DTI scenarios, resolve escalations, deliver training, create documentation, and collaborate cross-functionally to drive client success and process improvements.

Leads higher-education data transformation engagements as the senior data advisor. Responsibilities include executive and client leadership, scope and risk oversight, SQL development, data migration, source-to-target mapping, data quality, governance, architecture, and integration strategy. Advises on CRM, financial, analytics, and institutional data ecosystems; guides APIs, ETL/ELT, batch, real-time, and event-driven integrations; troubleshoots data and interface issues; mentors cross-functional teams; and supports sales and business development. Periodic client travel is required.

Owns the full enterprise sales cycle across named West Coast accounts, including prospecting, qualification, pipeline development, forecasting, negotiation, and closing. Maintains quota attainment, pipeline coverage, MEDDPICC discipline, and HubSpot opportunity hygiene. Builds account plans, partners with sales engineering and marketing, conducts technical discovery and proof-of-concept execution, and represents CIQ at customer meetings and regional events. The role is remote and home-based in California, with regular travel throughout the Western United States.

Build simulation and planning systems for complex communications networks. Develop tools that model hypothetical scenarios, vary configurations and assumptions, compare outcomes, surface tradeoffs, and identify risks. Design scalable, reliable backend systems for complex, evolving network states while collaborating across product engineering to integrate capabilities into broader workflows. Responsibilities span system design, implementation, testing, debugging, and operational support.

Own the success, retention, and growth of strategic K-12 district accounts. Build executive relationships, create customer success plans, drive product adoption, manage renewals and expansion, oversee complex implementations, analyze customer data, coordinate cross-functional teams, and provide strategic guidance on student safety and well-being solutions.

Build and validate AI-native tooling for utility power-engineering and go-to-market teams. The role combines customer discovery, workflow analysis, Python and SQL development, data investigation, prototypes, integrations, debugging, and production-quality software. You will partner with Product and Engineering, dogfood tools on live customer problems, define requirements and quality standards, lead rollout and adoption, train users, and establish the company’s forward-deployed engineering operating model. Regular customer and U.S. team travel is required.

Build and operate Modular’s multi-cloud, multi-tenant platform for distributed LLM inference. Responsibilities include developing fault-tolerant, low-toil backend services across cloud and hardware environments; improving observability from requests to kernels; optimizing cold starts; and creating Helm charts and Kubernetes operators. The role requires backend engineering, distributed systems, cloud infrastructure, Kubernetes operations, and machine learning experience.