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Tier-1 employer, popular backend role, mid-level experience, metro location, and broad AI/cloud skillset.
Core backend skills are transferable, but CAASM and cybersecurity domain specifics increase fit sensitivity to medium.
Explicit 5+ years, mandatory backend/cloud skills and agentic LLM expertise create high shortlisting strictness.
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Design and develop scalable microservices and integration frameworks for a Cyber Asset Attack Surface Management platform, enabling organizations to assess digital risk at enterprise scale.
Build and optimize APIs and data pipelines to correlate asset data with vulnerabilities, threat intelligence, and security findings from diverse sources.
Apply and operationalize large language models (LLMs) and agentic workflows to enhance engineering productivity, code quality, and ensure safe, reliable production-ready AI-assisted solutions.
Minimum 5+ years of production experience building and maintaining distributed systems at scale.
Strong proficiency in Go, Python, or Java with experience in microservices and cloud-native environments.
Hands-on experience with Kubernetes, Docker, infrastructure as code, event-driven architectures, and message queuing systems.
Work Experience Required: Minimum 5+ years explicitly mentioned; Notice Period: Not explicitly mentioned in the JD.
Experienced backend engineer with a focus on building high-throughput data processing and integration systems in cloud-native, security-oriented environments.
Demonstrated practical knowledge and application of LLMs and agentic workflows including design of guardrails and handling non-deterministic AI outputs.
Technical contributor comfortable with end-to-end ownership in a high-trust, complex engineering environment integrating security vendor and cloud provider data.