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High: Tier-1 brand, generic software title, and Bangalore metro location increase qualified applicant density.
High because specialty in security-focused data platforms and production LLM integration limits cross-industry transferability.
High due to required deep distributed-systems, Spark/Kafka, cloud (EKS/Terraform), and LLM/AI production experience.
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Architect and build a secure, cloud-native, highly scalable data platform to measure, mitigate, and reduce enterprise security risk by unifying disparate security data across multiple Salesforce and external environments.
Design and develop high-performance data pipelines ingesting security signals from diverse sources including vulnerability scanners, asset and identity management systems across AWS, GCP, Salesforce, and third-party vendor platforms.
Integrate AI/ML and LLM-driven capabilities for anomaly detection, agentic triage/remediation workflows, and risk scoring; provide technical leadership and mentor engineering team members in software development, security, and AI-assisted tooling.
Experience designing and operating high-scale distributed systems with high availability and fault tolerance.
Proficiency in Java or Scala programming and data technologies such as Apache Spark, Kafka, Hadoop, SQL/NoSQL.
Hands-on experience integrating AI/ML or LLM models into production systems including RAG pipelines or agent/tool-use frameworks.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in cloud-native data platform architecture involving multi-source security data ingestion and processing at scale.
Skilled in integrating applied AI/ML/LLM techniques to security data use cases with attention to system performance and security guardrails.
Able to lead engineering teams in adopting AI-assisted development tools and enforcing secure coding and architectural best practices.