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srisindhu manchikanti
Mid-level Machine Learning Engineer specializing in multimodal and time-series AI systems
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About
Backend engineer who rebuilt and refactored high-traffic systems at Phenom using Java/Spring Boot/Play and also designs Python/FastAPI services. Focused on measurable reliability and performance gains through DB/query optimization, async processing, and strong observability, with disciplined rollout practices (feature flags, parallel runs, rollback) and security patterns including token auth and row-level security.
Experience
Education
Key Strengths
- Backend architecture evolution for high-traffic systems (reliability, latency, extensibility)
- Database performance tuning (indexing, pagination, eliminating redundant queries) to reduce load and improve throughput
- Designing responsive APIs via async processing and offloading long-running work
- Safe refactors/migrations using feature flags, parallel implementations, and gradual traffic shifting with rollback readiness
- Defense-in-depth access control (token auth, roles/claims, service-layer checks, row-level security, auditing/logging)
- Identifying and hardening edge cases in async workflows (idempotency, retries, partial-failure handling) reducing production incidents
- Operational rigor: improved observability (logs/metrics) and easier debugging
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