Senior Integration Software Engineer
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Job Description
Senior integration engineer building microservice integrations for a global cybersecurity leader. Connecting SecOps platforms with cybersecurity tools through APIs, streaming, and AI automation.
Responsibilities:
- Own one or more integration domains end-to-end, including roadmap, architecture decisions, trade-offs, and delivery
- Identify problems, scope solutions, and drive them to completion
- Deliver robust, production-grade integrations supporting the growing customer base
- Develop microservice-based solutions using REST, GraphQL, streaming APIs, MCP, and LLM-powered automation
- Connect the platform with cybersecurity tools and third-party services
- Accelerate design and development using LLM-based coding assistants, AI-driven testing, and automated code review
- Automate builds, deployments, monitoring, and incident triage using AI and scripting
- Champion AI adoption across the team and help colleagues integrate AI tools into daily work
- Build internal tooling where it adds leverage and measure efficiency gains
Requirements:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
- 3+ years of backend software development experience
- Proficiency in Python, Go, or Java
- Strong foundation in building and operating production microservices
- Deep experience with API design and integration, including REST, GraphQL, streaming APIs, LLM APIs, and embedding services
- Experience with secure API patterns, including OAuth, API keys, and rate limiting
- Strong background in distributed systems, message queues such as Kafka or RabbitMQ, or orchestration frameworks such as Celery or Airflow
- Demonstrated regular production use of AI tools such as Copilot, Cursor, Claude, or ChatGPT to accelerate engineering workflows
- Judgment to assess when AI output is trustworthy and when human expertise is required
- Preferred: cybersecurity domain experience in SOAR, EDR, SIEM, XDR, or similar
- Preferred: large-scale data processing, real-time pipelines, or event-driven architectures
- Preferred: cloud platforms such as AWS, Azure, or GCP
- Preferred: containerized deployments using Kubernetes or Helm
- Preferred: AI-native integration patterns including MCP, function calling, or agent orchestration frameworks
- Preferred: experience building systems incorporating LLMs or AI services into workflows or product features
Benefits:
- Competitive salary
- Ample career growth opportunities
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