Top Tech Jobs & Startup Jobs

Supports the identification, launch, and scaling of new products and market opportunities. Responsibilities include coordinating cross-functional teams, analyzing client workflows and product performance, supporting customer adoption, developing go-to-market strategies, and managing project plans, milestones, deliverables, and success metrics. The role requires strong analytical, communication, execution, ownership, and adaptability skills in a fast-paced, in-office startup environment.

Manage purchasing and inventory across warehouse locations by analyzing sales trends, demand forecasts, stock levels, vendor capabilities, production schedules, and shipping timelines. Maintain SKUs and purchase orders, prevent stockouts and overstock, coordinate incoming inventory, and communicate inventory health across Logistics, Sales, Branding, Operations, vendors, factories, and the Asia office. Lead process improvements and support supply chain efficiency.

Leads revenue operations and GTM innovation by advising Sales, Marketing, and Customer Success; building AI-first systems, automations, dashboards, and workflows; analyzing funnel performance; improving forecasting and pipeline health; and driving cross-functional initiatives that increase GTM efficiency and revenue growth.

Lead the U.S. customer onboarding function by managing 5–6 Launch Representatives, owning deployment performance and ARR, improving launch efficiency and customer outcomes, and establishing scalable operating rhythms. The role involves coaching, capacity planning, process improvement, cross-functional collaboration with Sales, Support, Rev Ops, Product, and Engineering, and ensuring ranchers successfully adopt Halter’s platform.

Lead the design, analysis, prototyping, testing, and documentation of rotary and linear actuators for humanoid robots. Collaborate cross-functionally, mentor junior engineers, perform FEA and DVP&R, create GD&T drawings and BOMs, support pilot builds, and optimize designs for scalability and design for manufacture and assembly.

Commercial Data Scientist will develop machine learning models, analyze large healthcare datasets, identify clinician behavioral patterns, and create reusable data products. The role partners with Product, Data, Strategy, Insights, and Sales teams to deliver client-facing analyses and data-driven recommendations. Responsibilities include statistical analysis, production model development, complex SQL querying, scalable data processing, automation, and communicating technical insights through compelling visualizations and narratives.

Leads revenue operations across Sales, Partner, and Customer Success, owning pipeline management, forecasting, territory planning, KPIs, dashboards, systems, and process improvement. Partners with Finance, Analytics, Product, and leadership to translate go-to-market strategy into scalable execution. Manages AI-enabled sales tools, reporting, automation, operating cadences, and a high-performing operations team while driving revenue growth, retention, expansion, and customer outcomes.

Own the vision, strategy, and roadmap for Software Factory, an AI-agent product automating software maintenance and development workflows. Define agent workflows, human handoffs, trust and quality standards, evaluations, verification, context and memory models, and integrations with GitHub, Linear, Codex, and Claude Code. Partner with design partners and enterprise customers to drive adoption of AI-powered engineering workflows.

Provides customer service and client relations support while managing service requests, scheduling, affiliate communication, and complex work orders. Coaches and trains entry-level customer service representatives through job shadowing and on-the-job guidance, identifies performance improvements, reports training progress, and serves as a subject matter expert. Maintains accurate confidential data, supports shift handoffs, and contributes to team efficiency and positive workplace culture.

Operate and maintain AWS-hosted MERN applications and large-scale data workflows. Manage serverless and Spark-based pipelines, perform incident response and on-call duties, engineer automation to eliminate operational toil, ensure HIPAA/SOC2/HITRUST compliance, build observability and lead blameless post-mortems.