Senior Software Security Engineer
Posted
Jul 14, 2026 (Yesterday)
Seniority
Senior
Work Model
Hybrid
Type
Not Specified
Category
Salary
Not specified
Skills
Description
Role: Sr Software Engineer Location: London, UK ( 3 days hybrid) Candidate rate: GBP 350/day (Inside IR35) Duration: 6+ Months Description: Good technical skills in Java and Java frameworks with relevant experience in latest version of Java 17+ Ability to solve technical problems, performance bottlenecks Good with Technical design and standard coding practices and secure design Experience in Test frameworks and able to automate the API’s and performance testing(Added benefit) Experience in any observability platform like Dynatrace etc, able to create alerts and dashboards Able to explain the key metrics for observability of a service Ability to build CICD pipelines preferably in Github actions Cloud experience, preferably Azure but other cloud services also fine. Responsibilities: Build and optimize backend services using Java (Java 17+), Spring Boot/Micronaut Design RESTful APIs, asynchronous messaging systems, and microservices. Own performance, reliability, monitoring, and observability for critical services. Ensure high engineering standards: code quality, design reviews, testing, CI/CD, and best practices. System Design & Architecture Drive system design sessions, architecture reviews, and RFC processes. Make key decisions around data modelling, caching, scalability, security, and operational resiliency. Evaluate and adopt modern architectural patterns (event-driven, domain-driven design, API-first, cloud native). Essential skills/knowledge/experience: 10–15+ years of experience building large-scale backend systems. Strong expertise in Java, Spring Boot (or Micronaut/Quarkus), and JVM internals. Deep experience with distributed systems, concurrency, and high-performance architectures. Hands-on experience with message queues (Kafka, RabbitMQ, Pulsar), API design, and event-driven systems. Solid understanding of SQL/NoSQL databases, caching, and data modelling. Strong knowledge of cloud platforms (Azure) and container technologies (Docker, Kubernete.
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