Top Tech Jobs & Startup Jobs in NYC, NY

Own the company-wide revenue engine by connecting marketing, sales, member engagement, clinical capacity, billing, collections, and financial performance. Investigate discrepancies, improve forecasting and reporting, define trusted metrics, maintain BI dashboards, identify data quality issues, and translate analysis into cross-functional decisions. The role requires strong SQL, analytics, business judgment, communication, and comfort working independently with technical partners in a remote healthcare environment.

Own the full sales cycle across New York, New Jersey, and Connecticut, selling SaaS solutions to public school districts. Build relationships with education leaders, navigate complex procurement and funding processes, manage Salesforce pipeline forecasting, conduct meetings and demos, and partner with implementation, customer success, and marketing teams to drive customer outcomes and renewals.

Support the legal and compliance teams by advising business units on policy, preparing FINRA filings, managing personal trading programs, reviewing compliance requests, supporting onboarding/certifications, and improving compliance workflows and systems.

Lead AI consulting growth in the energy, oil and gas sector by advising executive clients, originating and expanding enterprise engagements, shaping AI use cases, managing commercial lifecycles and P/L, and overseeing delivery. Build strategic account plans, guide cross-functional consultants and technical teams, support thought leadership, and translate operational challenges into scalable solutions such as predictive maintenance, computer vision, safety automation, document processing, and digital twin pipelines.

Build and scale Dash0’s hyperscaler marketplace and cloud-native consultancy partnership programs. Manage AWS, GCP, and Azure relationships, develop co-sell motions, create SI incentives and enablement, drive partner-sourced and partner-influenced ARR, and provide partner intelligence to product, pricing, and positioning teams. The role is based remotely in Amsterdam or London and focuses on establishing repeatable partner revenue channels.

Growth leads will support fast-growing portfolio companies by driving growth initiatives. The role is suitable for candidates with marketplace experience, which is preferred. Applicants submit their details for consideration and may be contacted when a suitable portfolio-company opportunity arises.

Leads the engineering function for identity, compliance, and risk shared services. Owns roadmap, domain models, architecture, regulatory requirements, hiring, team development, incident response, threat modeling, and cross-functional partnerships with Product, Compliance, Legal, Security, and Risk. This player-coach role requires hands-on technical leadership in regulated financial systems, including identity, onboarding, AML, fraud, and risk decisioning.

Own the architecture and evolution of Crucible, building deployment systems, developer tooling, services, and platform abstractions. Lead technical roadmap development, solve complex deployment challenges, improve production reliability and security, and eliminate recurring operational issues. Provide hands-on technical leadership through system design, coding, code review, documentation, and engineering standards while improving developer productivity, deployment speed, platform adoption, and customer deployment success.

Own the research agenda for Ambral Labs’ replayable enterprise environment engine. Design experiments, build environment factories, develop graders and evaluation sets, mine tasks from historical workflows, optimize models and agent policies, advance long-horizon post-training methods, and scale replay and observability systems. The role combines hands-on research and production implementation while establishing research culture, recruiting talent, and working directly with the CTO on enterprise deployments.

Build and scale production Python pipelines for economic and financial climate-risk models. Responsibilities include transforming research prototypes into tested infrastructure, supporting statistical, econometric, and machine-learning modeling, cleaning large financial and hazard datasets, resolving data anomalies, and collaborating with engineering, product, and client teams to document outputs and communicate findings.