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Tirth Shah
Mid-level AI/ML Engineer specializing in anomaly detection, data tooling, and cloud-native systems
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About
Backend/platform engineer who built an LLM-driven QA automation system (“mockmouse”) using a Flask orchestration microservice, Socket.IO real-time updates, Redis caching, and strict Pydantic schemas to turn prompts into reliable action graphs and automated browser tests. Has hands-on Kubernetes delivery experience (Docker/Helm/Jenkins) and has supported large migration programs, validating ETL cutovers with 1M+ synthetic records and rigorous output comparisons; also built event-driven monitoring/anomaly detection streaming into Grafana.
Experience
Education
Key Strengths
- Designed Flask-based orchestration microservice converting user prompts into actionable tags and automated browser-driven QA
- Strong LLM pipeline engineering with strict Pydantic schemas to mitigate vague/incomplete model outputs
- Real-time backend/frontend integration using Socket.IO
- Kubernetes deployments of containerized microservices using Docker + Helm; built delivery pipelines with Jenkins
- Migration validation at scale using 1M+ synthetic records and schema/row/aggregate comparisons to ensure functional equivalence
- Built event-driven real-time metrics/anomaly detection streaming to Grafana; handled spikes with buffering and adaptive batching
- Practical GitOps implementation: declarative configs in Git, PR-based approvals, automated reconciliation, rollback via revert
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