Top Tech Jobs & Startup Jobs in London

Lead design and implementation of CI/CD pipelines, infrastructure automation (Ansible/Terraform), and containerised platforms (Docker/Kubernetes/EKS/AKS) on AWS. Monitor and optimize systems (DataDog), ensure security/compliance, troubleshoot environments, mentor engineers, and drive POCs for AI-assisted automation integrated into CI/CD, code validation, and incident resolution.

The Application Architect designs and guides application architecture for the Risk Intelligence platform, ensuring alignment with quality standards and effectively collaborating with teams and stakeholders.

The Principal Architect will design technical architecture solutions, assess business requirements, support vendor assessments, and ensure adherence to digital standards in Finance programmes.

Design, develop and deliver enterprise-grade software and AI-powered analytics for financial markets. Build full-stack solutions with CI/CD, automated testing and cloud deployments (AWS/Azure). Collaborate across regions, solve complex problems, and continuously learn new technologies to improve customer-facing data and analytics products.

The Senior Attack Monitoring Analyst monitors and responds to cyber security incidents, utilizing SIEM tools and threat intelligence to improve detection capabilities.

Lead quantitative research and index methodology design for equity and multi-asset strategies. Drive independent research, translate models into production with Engineering, build analytics and AI-enabled research infrastructure, support client engagements and business development, mentor team members, and contribute to strategic direction and product innovation.

Senior individual-contributor responsible for hands-on implementation, performance, scalability, resilience, and operational excellence of a Java/AWS-based Risk Screening platform. Partners with architects and SREs, leads complex changes, optimises large databases, and mentors engineering teams to ensure reliable, high-performance production systems.

Define and evolve end-to-end data architecture for real-time news ingestion, enrichment, storage, indexing, and distribution. Develop data standards, schemas, and contracts; normalize metadata for discoverability; ensure observability and lineage; influence platform strategy; collaborate with engineering and product leaders; pragmatically evaluate tools to improve reliability and performance.

Provides principal-level technical leadership for enterprise machine learning systems supporting a matching platform. Responsibilities include ML architecture, feature pipelines, model development, AWS SageMaker MLOps, low-latency inference, explainability, governance, security, monitoring, drift detection, testing, and deployment automation. The role mentors engineers, establishes engineering standards, and drives scalable, reliable, compliant ML platform capabilities across environments.

Design, build and maintain software and automation for control monitoring, testing, reporting and evidence collection. Integrate with security platforms (SIEM, IAM, EDR), cloud and engineering tools, develop APIs, CLI tools and data pipelines, and translate technical control activity into auditable evidence and reporting to reduce manual audit and assurance effort.