Top Tech Jobs & Startup Jobs

Lead design, validation, deployment, and monitoring of fraud prevention ML models and analytical frameworks. Partner with product, tech, and commercial teams to deliver scalable, governance-aligned solutions for identity, entity resolution, and risk decisioning. Mentor data scientists, support customer engagements and proofs of concept, and drive roadmap, innovation, and Responsible AI compliance across global regions.

Develop and manage integrated multi-channel marketing campaigns, optimize performance using data and audience insights, manage budgets and key account relationships, collaborate with content, creative and data teams, and continuously improve campaign effectiveness.

Senior MLOps engineer to productionize NLP/GenAI models and RAG systems: build and automate ML pipelines, CI/CD, model registries, search/vector/graph-based retrieval, evaluation metrics and cost-optimized scalable infrastructure, collaborating with data scientists, product and operations teams.

Design and implement graph-based search services and scalable backend systems using Java and Spring Boot. Build GraphQL/REST APIs, integrate with AWS services and databases, ensure observability with New Relic and Coralogix, mentor engineers, and collaborate on search and recommendation features to deliver reliable, cloud-native solutions.

Lead a software engineering team to design, build, and operate AI-powered features (LLM integrations, RAG pipelines, agents). Write and review complex code, drive AI system evaluation and hallucination mitigation, oversee data ingestion/embedding/indexing pipelines, mentor engineers, manage projects and staff, and implement development best practices and secure, scalable AI architectures.

Lead functional, automated, and performance testing for a large-scale data platform. Develop test strategies, automation, and performance solutions; validate data quality and formats; test microservices, event-driven systems, and distributed processing; collaborate across Product, Engineering, and Ops to ensure reliability and continuous improvement.

Serve as a strategic, consultative Customer Success Manager for large law firm accounts, driving adoption of LexisNexis drafting, research, analytics, and AI workflows. Build trusted advisor relationships, create success plans, lead change management, use data to monitor health and identify growth or churn risks, and partner cross-functionally to improve products and retention.

Lead a global Learning & Performance team to design and deliver a sales and customer success curriculum, embed Challenger methodology, build assessments and certifications, align learning with commercial strategy, use data to measure impact, and partner cross-functionally to drive sustained behaviour change and performance.

Drive new partner sales and revenue growth in DACH by prospecting, building pipeline, managing territory plans, converting leads to closed contracts, forecasting, and supporting onboarding and retention in collaboration with presales and partner success teams.

Designs, deploys, and maintains production-grade ML/AI systems and MLOps workflows. Converts prototypes into scalable services, implements LLM/agent-based and RAG solutions, integrates models with APIs and microservices, monitors model performance, and collaborates across teams to ship features and resolve complex production issues.