Top Tech Jobs & Startup Jobs in NYC, NY

The Cloud Inference Engineer is responsible for building and maintaining a scalable LLM inference platform, focusing on distributed systems and machine learning technologies while collaborating across teams to optimize performance.

Own the full B2B SaaS sales cycle, from prospecting through negotiation and close, while meeting quotas and acquiring automotive dealership customers. Present AI solutions and ROI cases to executives, build pipeline through cold outreach, expand accounts through cross-selling and upselling, and collaborate with Client Success and Solutions Engineering. The role requires technical aptitude, complex deal experience, strong negotiation skills, and comfort working in an ambiguous early-stage startup.

Build, test, maintain, and enhance Workday financial reports, dashboards, and reporting solutions. Gather requirements, validate and reconcile data, document report logic, troubleshoot performance issues, support Workday implementations and releases, and train end users. Partner with Finance, HR, Supply Chain, and other stakeholders to ensure accurate, compliant, and actionable reporting across a nonprofit healthcare system.

Leads company-wide pricing and packaging strategy across products and verticals. Sets monetization vision, discounting guardrails, rate cards, bundling approaches, and pricing approval processes. Partners with executive, product, sales, marketing, customer success, and finance leaders to drive alignment, improve deal velocity, increase profitability, and support retention. Builds financial models, reporting, enablement programs, and implementation plans while adapting strategies to company goals.

Leads strategic, cross-functional programs for the Pricing & Inventory team, from opportunity discovery and beta testing through companywide scale. Translates business goals into roadmaps, coordinates data science, engineering, product, and business teams, manages timelines and trade-offs, and presents recommendations to executive leadership. Uses structured analysis, experimentation, and measurable outcomes to drive decisions in ambiguous environments.

Own Veeam’s global enterprise partner marketing strategy for its Data & AI Security portfolio. Build scalable partner go-to-market playbooks, define partner profiles and growth strategies, lead product launch readiness, create messaging and enablement assets, develop integrated campaigns, and drive partner-sourced and partner-influenced pipeline. Collaborate with sales, product marketing, alliances, channel, demand generation, and regional teams while tracking activation, campaign performance, and adoption metrics.

Administers and improves employee benefits and leave programs, including health, retirement, disability, FMLA, accommodations, and annual enrollment. Ensures regulatory compliance, data accuracy, payroll reconciliation, vendor performance, employee communications, and timely case resolution. Partners with HR, Payroll, Legal, managers, employees, third-party administrators, and HRIS teams on complex cases, system testing, reporting, wellness programming, and process improvements.

Manage federal service contracts valued at approximately $5M–$10M, overseeing daily operations, staffing, finances, deliverables, quality assurance, reporting, risk mitigation, and customer satisfaction. Supervise employees, monitor budgets and profitability, support billing and invoicing, and assist with proposals, follow-on opportunities, and business development. The role works with the Prime Program Manager and requires occasional travel.

Leads the design and delivery of scalable data pipelines, dbt models, orchestration workflows, and analytical data models. Establishes data architecture, engineering standards, quality frameworks, governance, observability, and self-service analytics practices. Partners with stakeholders, leads technical reviews, mentors engineers, supports hiring, oversees analyses, and participates in incident response and continuous improvement.

Own product strategy and backlog modernization for the VA Loan Guaranty technology portfolio. Translate policy and stakeholder needs into prioritized roadmaps, precise user stories, acceptance criteria, and executable plans. Coordinate releases, UAT, analytics, legacy decommissioning, and configuration-versus-customization decisions across VA, lenders, servicers, architecture, and engineering. Apply AI tools to policy analysis, requirements drafting, and feedback synthesis while respecting federal security and privacy boundaries.