Top Tech Jobs & Startup Jobs

Build responsive, accessible React frontends and Node.js backend services; use AI-assisted development tools responsibly to accelerate implementation, testing, and refactoring; follow TDD, CI/CD, and automated testing; collaborate with UX, product, and QA; contribute to hiring and knowledge sharing for the London engineering team.

Lead an embedded AI squad from discovery to production: harden and deliver AI prototypes, design reusable agentic AI patterns and architectures, ensure security/data governance, integrate AI into enterprise systems, codify reference implementations, mentor engineers, and measure outcomes to scale solutions across the organization.

Lead analytic projects and teams, review and approve models, define frameworks, methodologies and governance, design LLM/RAG/agentic AI systems with knowledge-graph and embedding integration, ensure evaluation, cost-performance optimization, AI observability, and compliance-aware production deployment while mentoring staff and communicating with senior stakeholders.

Lead complex, customer-facing projects from initiation through delivery. Manage schedules, risks, dependencies, governance, stakeholder communications, scope/change control, compliance, and executive reporting. Drive cross-functional alignment, issue resolution, and PMO best practices while operating in fast-paced, regulated environments.

Lead a team of 4-5 ML engineers to design, build, and operate scalable AI/ML systems and agentic architectures. Provide architecture and code guidance, establish ML engineering best practices, standardize LLM serving and retrieval infrastructure, implement safety guardrails and traceability, define evaluation frameworks for reasoning quality, and ensure CI/CD, data governance, and responsible AI compliance.

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.

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.

Own end-to-end product capabilities for AI-powered legal drafting and analytics. Drive customer discovery, prioritize requirements, define hypotheses and A/B tests, build business cases, coordinate launches, and deliver training and go-to-market activities to expand Protege product features.

Full-stack engineer to build a scalable web portal: develop responsive React/TypeScript/Tailwind UIs and a shared component library; design Java Spring GraphQL back-end for file upload workflows, job tracking, retries, storage, and results retrieval; implement secure auth, testing (Jest, Playwright), CI/CD, observability, accessibility (WCAG AA), and documentation.