Top Tech Jobs & Startup Jobs

Own agentic AI products end to end, from customer discovery and AI prototyping through delivery, launch, and iteration. Define product strategy, success metrics, and priorities; collaborate closely with engineering, design, commercial teams, and customers; coordinate go-to-market enablement; analyze usage data and feedback; and use AI and agentic tools to accelerate research, prototyping, and product development.

Drive new business sales for CUBE Intel’s mid-market SaaS solution. Responsibilities include prospecting, territory planning, managing full sales cycles, engaging senior compliance stakeholders, negotiating and closing deals, maintaining CRM discipline, forecasting pipeline, improving conversion rates, and contributing to go-to-market strategy. The role requires proven B2B SaaS sales experience, strong communication and negotiation skills, and the ability to manage complex, multi-stakeholder sales cycles.

Serve as the professional first point of contact for the London office while supporting reception, office operations, visitor management, supplies, onboarding, and events. Provide growing executive assistant support to C-Suite leaders through calendar and meeting coordination, travel arrangements, correspondence, expense processing, leadership meeting logistics, and confidential administrative projects.

Own the full customer relationship from initial engagement through implementation, delivery, and business-as-usual transition. Lead client meetings, workshops, requirements gathering, platform demonstrations, stakeholder management, issue resolution, and service delivery. Collaborate with legal, finance, technology, partners, and offshore teams while advocating for customer needs and influencing the product roadmap. Support UAT, continuous improvement, and regulatory technology implementations for financial services clients.

Lead quality assurance initiatives for regulatory data products, ensuring high accuracy, SLA adherence, compliance, and consistent QA standards. Develop QA strategies, mentor team members, manage resources, report quality metrics, mitigate data risks, coordinate automated data quality checks, and improve documentation and processes across international teams.

The Data Quality Analyst profiles data, creates quality rules, monitors dashboards, investigates anomalies, identifies root causes, and performs controlled data corrections. The role improves SSIS/ETL ingestion pipelines, validates production data, documents governance and remediation procedures, and collaborates with technology, product, compliance, and business teams. It also supports AI-enabled monitoring and automation to improve data accuracy, reduce recurring defects, strengthen audit outcomes, and enhance customer-facing services.

Perform quality assurance reviews of regulatory data, meeting accuracy and SLA targets. Analyze datasets to identify errors, inconsistencies, and anomalies; collaborate with Data Quality and governance teams to implement controls, validations, and automated checks. Identify recurring issues, recommend process improvements, support automation initiatives, and improve QA documentation while ensuring compliance with data management policies and regulations.

Develop and maintain C#/.NET web scraping solutions that extract structured regulatory data from complex HTML websites. Troubleshoot dynamic, multilingual, access-restricted sites and improve caching, performance, automation, and reliability. Ensure extraction accuracy, document code and testing, manage tasks and deadlines, and collaborate with analysts, QA, and engineering teams. The role offers mentorship while progressively increasing responsibility for technical scraping and automation work.

Own the end-to-end production lifecycle of machine learning models and LLM integrations. Build Azure-based ML pipelines, deployment and serving infrastructure, monitoring, drift detection, rollback systems, experiment tracking, and model governance. Manage LLM providers, gateways, prompt versioning, observability, token usage, and costs. Partner with data scientists and engineers to establish MLOps practices, CI/CD, infrastructure as code, automated testing, reliability, and operational efficiency.

Converts complex PDF regulatory documents, including scanned and multilingual content, into accurate, accessible HTML. Responsibilities include handling tables, images, lists, footnotes, OCR issues, coding tasks in HTML, CSS, C#, .NET, and JavaScript, debugging, testing, quality assurance, documentation, and code reviews. The role also supports task management, collaboration with QA and project teams, and adoption of AI-driven tools to improve conversion efficiency and output quality.