Senior Software Engineer (JAVA)

About Behavox Behavox is a cloud-native AI company providing an integrated controls platform for global banks, asset managers, hedge funds, private equity firms, insurance businesses, and commodity firms. The platform unifies communications and trade surveillance, compliant archiving, policy management as well as front-office analytics on a single, AI-native technology stack, delivered as a globally scalable SaaS-based cloud service. At Behavox, our engineering culture is built around speed, experimentation, and technical excellence, following agile principles and rapid iteration. We constantly test and adopt the latest cloud technologies and AI tooling, optimising for fast feedback loops and execution. We look for people who can move fast, challenge conventional wisdom, and who want to work at the frontier of modern AI, SaaS platforms, and distributed systems. Behavox is a high-performance organisation with a strong bias toward delivery, ownership, and responsibility. We commit, and we execute. We are building systems that are complex, mission-critical, and global in scale; systems that many consider too large or too difficult. To do that, we seek the smartest, most technically capable engineers and technologists who take end-to-end responsibility and want to win by building what others cannot. Founded in 2014 and backed by SoftBank Vision Fund, Behavox is headquartered in London, with offices worldwide, including New York City, Montreal, Seattle, Singapore, and Tokyo. About the Role The Software Engineer (Java) operates at a senior engineer level, driving technical direction across core product domains. The role combines deep hands-on Java engineering with architectural ownership — from high-level system design and technology selection to leading delivery of critical, cross-cutting platform capabilities. At this level, engineering excellence extends beyond implementation: the engineer determines the right approach to complex problems, communicates technical decisions across functions, participates in hiring, and is accountable for the long-term health of the systems they own. This level demands sound judgment on technology and business trade-offs and the ability to act as a technical lead. A defining expectation is mastery of AI-assisted engineering — leveraging agentic AI tools as force multipliers while retaining full ownership of architecture, quality, and technical outcomes. What You'll Bring Expert Java engineering: Deep understanding of Java internals — GC tuning, Collections Framework, advanced concurrency (java.util.concurrent, multithreading), NIO/NIO2, performance profiling, and heap-dump analysis. Mastery of Spring Framework (IoC/DI, bean lifecycle, Spring Boot). SOLID principles, Clean Code practices, and GoF design patterns Software architecture and design patterns: Expertise in monolith and microservices architectural styles — including migration patterns and domain-driven decomposition. Inter-process communication design (REST, gRPC, messaging), transaction management in distributed systems (Sagas, 2PC), CQRS, Event Sourcing, and external API design focused on scalability, security, and documentation Cloud-native platforms and infrastructure: Experience designing high-availability and high-load systems on GCP (preferred), AWS, and Azure. Cloud security best practices: IAM, VPC, data encryption, JWT/JWS/JWE. Infrastructure as Code (Terraform or equivalent) and Twelve-Factor App methodology Observability, reliability and deployment: Implementing full observability stacks: structured logging, distributed tracing, metrics, and alerting. SLI/SLO/SLA frameworks. Deployment strategies: Rolling Updates, Blue/Green Deployments, Canary Releases AI-assisted engineering: Practitioner-level command of agentic AI tools applied to software engineering — encompassing prompt engineering techniques, AI context management and its limitations, sub-agents, skills and plugins, multi-agent orchestration, and team-of-agents architect