Top Tech Jobs & Startup Jobs

Process card-update requests through a web application by manually refreshing card information to trigger API updates. Track requests, meet 2–3 business day SLAs, maintain records, follow documented procedures, and escalate exceptions. The role requires accuracy, reliability, basic computer skills, communication, adaptability, and availability during US business hours. This is a remote, six-month contract with an evening EST shift.

Manage end-to-end, high-volume technical recruiting across LATAM, focusing on AI, data, BI, and software engineering roles. Source and screen candidates, coordinate interview pipelines, partner with U.S. hiring managers, maintain ATS records, and ensure strong candidate experiences. The role also requires Mexican market expertise to provide recruiting guidance and support regional growth.

Conduct supplier outreach to convert paper-check payments to commercial card and ACH methods. Explain payment options, answer questions, facilitate enrollment, manage follow-ups, document cases, and coordinate with suppliers, business customers, and internal teams. Research records, resolve routine issues, escalate exceptions, provide reporting data, and follow financial-services compliance and quality procedures while managing high-volume workflows.

Supports month-end close, general ledger maintenance, reconciliations, financial reporting, accounts payable, collections, payroll, tax activities, and audit preparation across multiple entities. The role uses NetSuite, FloQast, Excel, and Yooz while coordinating with accounting, billing, revenue recognition, tax advisors, and external stakeholders. It also emphasizes process optimization, automation, accuracy, and managing recurring monthly deadlines.

Lead the architecture, development, and production deployment of generative AI solutions using LLMs, transformer models, RAG pipelines, and agentic workflows. Design scalable cloud deployments, establish prompt engineering and evaluation practices, implement Responsible AI guardrails, and monitor model performance. Collaborate with engineering, product, data science, and MLOps teams to move solutions from prototypes to production. Mentor engineers and promote maintainable Python development, experimentation, KPI definition, and data-driven decision-making.

Lead the design, development, and production deployment of generative AI solutions using LLMs, transformer models, RAG pipelines, and agentic workflows. Build scalable multi-step AI agents, implement responsible AI guardrails, optimize cloud deployments, establish evaluation and monitoring practices, and collaborate with engineering, data science, MLOps, and product teams. Provide technical leadership while promoting maintainable Python code, experimentation, and data-driven decision-making.

Design, build, deploy, and maintain production-grade generative AI solutions using LLMs, transformers, RAG pipelines, and agentic systems. Develop prompts, evaluation frameworks, safety guardrails, and multi-step workflows integrating tools and APIs. Deploy and monitor AI applications across cloud environments while optimizing accuracy, cost, latency, reliability, and safety. Collaborate with Product, Engineering, and ML Ops to move prototypes into scalable production systems.

Lead end-to-end data science and AI initiatives focused on marketing optimization, predictive modeling, experimentation, and analytics. Partner with clients and cross-functional teams to translate business needs into solutions, build data pipelines, deploy machine learning and GenAI systems, and develop evaluation and safety frameworks. Manage people, project plans, stakeholder communication, and client-ready deliverables while supporting production ML and LLM applications.

Design, architect, and deploy production-grade generative AI solutions using LLMs, transformer models, RAG pipelines, and agentic workflows. Develop multi-step AI agents, optimize cloud deployments, establish prompt engineering and evaluation practices, monitor model performance, and implement responsible AI guardrails. Collaborate with data science, engineering, MLOps, and product teams to move solutions from prototype to production while supporting maintainable Python development and data-driven AI initiatives.

Leads and mentors data scientists while overseeing end-to-end delivery of advanced analytics solutions. Develops pricing, segmentation, predictive, Bayesian, causal inference, marketing mix modeling, and optimization models. Deploys solutions through AWS SageMaker, establishes model governance and quality standards, and partners with clients and senior stakeholders to translate analytical findings into measurable business outcomes.