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NITEESHA THOTTEMPUDI
Mid-level Software Engineer specializing in full-stack cloud-native systems
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About
Backend/platform engineer from Dune Security with strong experience turning messy, fragmented workflows into reusable production systems. They’ve built a shared database abstraction layer, integrated multiple enterprise security platforms into a unified workflow, and shipped AWS Bedrock-powered security insight features with guardrails and human review.
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Key Strengths
- Owned reusable database abstraction layer across multiple services
- Improved response times by ~40-60% through caching and query optimization
- Strong production backend engineering with Django, Redis, MongoDB, and PostgreSQL
- Incremental rollout and migration strategy for high-risk production changes
- Data-driven stakeholder communication using Datadog metrics
- Legacy integration experience across CrowdStrike, Okta, Microsoft Entra, and Defender
- Built normalized internal data models from inconsistent external APIs
- Production-grade testing, monitoring, logging, and rollback discipline
- LLM feature integration with AWS Bedrock and human review guardrails
- Balances standardization with flexibility in multi-service platform design
- Designed modular Flask backend with clear routing/service/data-access boundaries
- Built batch-oriented automation using Airflow DAGs with retries, SLAs, and monitoring
- Containerized services and managed dependency/version consistency across Flask and Airflow
- Improved ORM performance by eliminating N+1 queries via explicit joins and indexing
- Reduced device-activation latency from ~1–2s to ~150–200ms (Comcast) through query/model optimization and caching
- Integrated ML inference into backend systems using REST/gRPC and Kafka telemetry streams
- Implemented schema validation, normalization, fallbacks, and confidence thresholds to make ML outputs safe/actionable
- Designed multi-tenant data isolation using validated tenant IDs and Postgres RLS
- Mitigated noisy-neighbor multi-tenant performance issues with tenant-first indexes and partitioning high-volume tenants
- Optimized high-throughput background processing with Redis caching, batched Kafka consumption, and parallel idempotent workers
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2 publications
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