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Fahad Altaf
Principal DevOps Architect specializing in cloud platform engineering and SRE
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About
End-to-end engineer focused on AI-native enterprise systems, including a production generative knowledge platform using RAG + semantic search over internal documentation (React, Python/Flask, GPU-hosted NLP models, Pinecone) with strong CI/CD and observability. Reports concrete outcomes including 40% faster knowledge access and ~75% employee adoption, and has led incremental cloud-native modernization using feature flags, parallel runs, canary releases, and regression testing.
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Key Strengths
- Owned and architected an enterprise generative knowledge platform end-to-end (frontend, backend, data, infra)
- Production RAG + semantic search implementations using vector DBs (Pinecone, ChromaDB) and transformer embeddings
- Built CI/CD with Jenkins enabling continuous deployment with zero downtime
- Implemented production observability (CloudWatch, logging, Grafana dashboards) tracking response time, error rates, and query accuracy
- Delivered measurable adoption and productivity impact: 40% faster knowledge access; ~75% employee active usage; ~5% reduction in manual effort
- Legacy modernization to cloud-native via incremental refactors with parallel run, feature flags, automated regression tests, canary releases, and load testing
- Handled cross-team delivery with minimal oversight using prioritization frameworks, daily standups, time-blocking, and short sprints
- Designed evaluation/guardrails for LLM systems: continuous evaluation, human-in-the-loop feedback, confidence scoring, and sensitive-data human validation
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