Senior Software Engineer, Intelligence Services
New
United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- AWSDockerPythonGCPKafkaKubernetesGoCI/CDMicroservices
Requirements
- Bachelor’s or Master’s degree in Computer Science or a closely related technical field.
- Strong experience with object-oriented and functional programming concepts, with preference for experience in functional programming languages such as Clojure.
- Proven experience developing production software systems using languages such as Clojure, Go, Python, or similar technologies.
- Experience designing and developing cloud-based applications on platforms such as Google Cloud Platform, Amazon Web Services, or Microsoft Azure.
- Strong understanding of distributed systems, microservices architectures, event-driven design, and message-based platforms such as Kafka or AMQP.
- Experience working with containerized applications, Docker, Kubernetes, and cloud-native development practices.
- Familiarity with CI/CD pipelines, GitOps workflows, and tools such as CircleCI, FluxCD, or ArgoCD.
- Experience working with relational databases, NoSQL databases, and search technologies.
- Strong knowledge of software engineering fundamentals, including algorithms, data structures, testing, and problem-solving.
- Experience working in agile product environments with small, collaborative engineering teams.
- Ability to write clear, maintainable, secure, and well-tested code.
- Familiarity with Linux-based operating systems and scripting languages such as Bash, Ruby, or Python.
Responsibilities
- Develop backend services, Kubernetes-based applications, and distributed systems supporting streaming data pipelines and cybersecurity analytics.
- Build scalable cloud-delivered products that leverage threat intelligence, data processing, and automation to improve security outcomes.
- Design and implement clean, maintainable REST APIs and microservices with clearly defined interfaces and reliable performance.
- Contribute to architecture decisions involving event-driven systems, cloud-native platforms, databases, and application infrastructure.
- Develop secure, testable, and production-ready code through continuous integration and continuous delivery practices.
- Apply AI-enabled development approaches to increase engineering efficiency and product impact.
- Participate in innovation initiatives from early research and ideation through implementation, scaling, and production delivery.
- Work collaboratively within agile engineering teams using modern development practices such as trunk-based development, GitOps, and DevOps workflows.
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