Top Tech Jobs & Startup Jobs

Leads workforce management strategy for a high-volume contact center, overseeing forecasting, capacity planning, scheduling, real-time staffing, reporting, and service-level performance. Manages WFM analysts, partners with Operations, HR, and Finance on staffing plans, identifies operational risks, supports contingency planning, and drives process improvements through automation, analytics, and optimized workflows.

Supports attorneys by conducting legal research, drafting contracts and court documents, organizing case files, tracking deadlines, communicating with clients, and preparing materials for hearings and trials. The role also includes scheduling, calendar management, correspondence, and other administrative legal support. Candidates need paralegal education or related training, legal research database experience, strong organizational and communication skills, document accuracy, and confidentiality.

Writes and optimizes copy for email campaigns, sales funnels, social media, advertising, and other marketing channels. Analyzes funnel and email performance, conducts A/B testing, and improves conversion, click-through, and open rates. Develops and manages marketing campaigns, supports budgets and marketing plans, collaborates with company leaders, and applies SEO, digital marketing, research, reporting, and project management skills.

Leads BPO sales strategy, enterprise client acquisition, strategic partnerships, solution development, market expansion, and sales team performance. Builds C-suite relationships, negotiates complex outsourcing contracts, manages KPIs and budgets, collaborates cross-functionally, and represents the company at industry events. Requires extensive travel and deep BPO market expertise.

Leads BPO sales strategy, enterprise client acquisition, strategic partnerships, solution development, market expansion, and revenue growth. Oversees sales team development, KPIs, budget allocation, cross-functional collaboration, and executive relationship management. Represents the company at industry events and drives customized outsourcing solutions for complex enterprise clients.

Develop, deploy, and optimize scalable machine learning solutions, including predictive, supervised, unsupervised, and deep learning models. Build data pipelines, production model-serving infrastructure, monitoring, retraining, and lifecycle processes. Ensure AI solutions meet quality, security, compliance, governance, and responsible AI standards. Research emerging technologies and collaborate with data scientists, engineers, product teams, and business stakeholders to deliver measurable business value.

Oversee and optimize infrastructure supporting AI and machine learning platforms, including servers, cloud environments, compute resources, GPU/CPU allocation, security controls, monitoring, incident response, and scalability. The role supports model deployment and training workloads, automates infrastructure operations, troubleshoots complex systems, maintains compliance, mentors administrators, and recommends architecture improvements. Candidates need at least five years of systems or infrastructure administration experience and expertise in cloud, virtualization, Linux, Windows, networking, storage, containers, and enterprise-scale environments.

Leads AI data annotation operations, including workflow management, resource allocation, production tracking, quality assurance, guideline development, audits, and corrective actions. Coaches annotation teams, supports recruitment and onboarding, collaborates with AI engineers and product teams, translates requirements into operational plans, and drives process improvements, automation, tool adoption, and data strategy initiatives.

Supports responsible AI governance by developing policies, maintaining control frameworks, conducting AI risk assessments, monitoring regulatory compliance, preparing reports, and advising legal, compliance, security, AI, and business stakeholders. The role also tracks governance metrics, supports audits, researches emerging regulations, and recommends improvements to AI governance programs.

Leads operational oversight, performance analysis, governance, and continuous improvement for AI-powered products and platforms. The role develops performance frameworks, dashboards, executive insights, forecasts, and operating standards while identifying risks and optimization opportunities. It partners with AI engineers, product teams, and business leaders, supports governance and audit activities, improves workflows, and contributes to scalable AI operating models and transformation initiatives.