Top Tech Jobs & Startup Jobs in NYC, NY

Lead budgeting, forecasting, and variance analysis while building AI-driven financial models, scenario planning, KPIs, and dashboards. Automate FP&A processes, deliver insights to senior leaders, and collaborate with cross-functional teams to improve forecast accuracy and strategic decision-making.

Lead architecture, development, and delivery of enterprise-scale real-time streaming solutions using Apache Flink and Java. Manage and mentor engineering teams, design fault-tolerant distributed systems, implement stream processing pipelines, and ensure performance, scalability, and production reliability. Collaborate with stakeholders across product, DevOps, and architecture to drive technical roadmaps and best practices.

Seeking an Engineering Manager or Principal Engineer to drive technical advancement. Must have extensive Java, Apache Flink, and Rust experience, strong background building scalable distributed systems, proven leadership, and a high-ownership, builder mindset in a security-focused company.

Serve as the internal customer advocate and technical pre-sales lead for finance-heavy billing and revenue recognition solutions. Translate complex billing and revenue requirements into configured demos, sandbox environments, and solution documents. Partner with Sales, Product, and Engineering to support discovery, RFPs, implementations, and handoffs for enterprise customers.

Provide clinical expertise to improve AI mental-health tools: annotate clinical interactions, evaluate psychotherapy datasets, design psychological testing scenarios, apply CBT frameworks, collaborate with engineers, ensure ethical standards, and drive research-backed AI improvements.

Serve as a domain expert in electrical engineering to identify and close knowledge gaps in LLMs. Collaborate with research teams to design and evaluate complex problems, provide detailed written feedback, and improve AI model performance. Remote, contractor role with weekly pay and flexible hours.

Design, implement, and optimize AI-driven solutions across the claims lifecycle (intake, investigation, adjudication). Build ML models for data extraction, fraud detection, reserve setting, subrogation, and adjudication decision engines. Collaborate with underwriting, fraud, legal, and IT to integrate models into operations and improve efficiency, accuracy, and compliance.

Drive data-informed capital allocation by building financial models (NPV, IRR), applying AI/ML for forecasting and scenario planning, creating build-vs-buy and prioritization frameworks, implementing decision-support systems, collaborating with cross-functional stakeholders, and monitoring post-investment performance to refine allocation models.

Guide research teams to close knowledge gaps in Statistics for LLMs: design and evaluate complex statistical problems and solutions, and provide clear written feedback to improve AI model performance.

Support the executive by cutting administrative workload 50% within 30 days, convert tribal knowledge into SOPs, manage weekly/6-month/2-year OKRs and org chart, configure productivity tools, proactively solve problems, and ensure clear, error-free communication across teams.