Mid-level SOC Analyst specializing in SIEM detection, threat hunting, and incident response
USASecurity Engineer5 years experienceMid-LevelCybersecurityHealthcareHealthcare IT
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About
Backend/AI engineer with production experience in payments/reporting systems and high-scale Node/NestJS services on AWS (ECS/ALB) using PostgreSQL, Redis, Kafka, Prisma, and Datadog. Shipped applied AI features including a Zendesk-embedded support copilot (summarization, draft replies, internal doc retrieval, playbook next steps) and an LLM-driven ops workflow agent with robust error taxonomy, retries/escalation rules, and auditability.
Experience
Security EngineerUnitedHealth Group
SOC AnalystHexaware Technologies
SOC AnalystAdons Softech
Education
Trine universitymaster, Cyber Security & Information (2024)
Vidya Jyothi institution of technologybachelor, Mechanical Engineer (2021)
Key Strengths
Built and operated high-scale backend services (~8–12M requests) on AWS ECS with PostgreSQL/Redis/Kafka
Deep performance debugging: traced P95 latency spikes to Prisma N+1 queries and missing/incorrect composite index usage; used Datadog APM and EXPLAIN to remediate
End-to-end ownership of an AI support copilot embedded in Zendesk (ideation, model selection, integrations, deployment, feedback loop)
Designed reliable multi-step LLM-driven ops automation with explicit planner/executor/verifier separation and deterministic error-handling policies
Production engineering discipline: risk-based testing, contract testing, failure-path testing, and strong observability/on-call practices
AI production guardrails: prompt/model versioning, continuous evaluation/monitoring, fallbacks, human-in-the-loop defaults, and audit logs
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