Top Tech Jobs & Startup Jobs

Manage design, implementation, and governance of global sales compensation plans. Lead quota setting, incentive modelling, payments, performance analysis, documentation, training, and cross-functional stakeholder engagement to ensure fair, motivating, and compliant programs.

Drive new enterprise client acquisition for AI-driven workflow and decision-support solutions. Own C-suite engagement, consultative discovery, executive-level positioning, and deal conversion across complex, multi-stakeholder buying environments while partnering with AI, product, and solution teams to scale repeatable new-logo sales motions.

Drive revenue growth by prospecting within an assigned territory, building pipeline, managing territory business plans, guiding prospects through the sales cycle to close, and maintaining customer relationships for retention, upsell and cross-sell. Log activity in CRM, submit forecasts, and support onboarding and implementation with internal teams.

Lead design and productionization of scalable ML/LLM systems for legal products. Build LLM applications (RAG, agents), hybrid search, model serving, data pipelines, APIs, and cloud-native infrastructure. Optimize for latency, reliability, and cost; establish deployment/observability best practices; partner with data scientists and provide technical leadership and coaching.

Client-facing strategic role partnering with in-house legal leaders at Fortune 1000 firms to demonstrate and sell LexisNexis AI and Workflow solutions, conduct discovery and tailored demos, drive revenue and upsells, track implementations, and inform product and market strategy.

Design, build, and maintain scalable data pipelines and services for large-scale search and analytics. Develop batch and ELT/ETL workflows, use Spark, Airflow, Python/Java and SQL, apply software engineering practices, contribute to AWS cloud systems, and collaborate with product and data science teams while mentoring engineers.

Lead architecture design and governance for large-scale, distributed, cloud-native systems. Define technical direction, standards, and best practices; align Enterprise Architecture with engineering teams; mentor developers; drive performance, resilience, and cost optimizations; evaluate emerging technologies (including AI/LLM integration); and lead resolution of complex technical issues while promoting reusable platform capabilities.

Design and evolve software and system architecture, evaluate and introduce new technologies, lead cross-functional teams to troubleshoot complex issues, monitor system health, and drive architecture direction and shared infrastructure initiatives.

Lead enterprise product adoption and operational readiness for Global Business Systems (CRM, CPQ, ERP, eCommerce). Design AI-supported, data-driven adoption frameworks, define go-live and post-launch readiness, track adoption KPIs, partner across Product, Technology, and business functions, and lead a team to drive measurable adoption and time-to-value.

Lead a small-to-medium data science team to design, develop, and deploy advanced AI/ML solutions (especially LLMs/Transformer models), mentor junior staff, define methodologies and governance, collaborate cross-functionally, and set team strategy and high standards for model development.