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Fahad Ahmad Siddiqui

Available to hire

I’m Fahad Ahmad Siddiqui, a software engineer based in Islamabad who enjoys taking systems across boundaries—mobile, backend, ERP, and infrastructure—and turning the hard parts into reliable, repeatable processes.

About

I’m Fahad Ahmad Siddiqui, a software engineer based in Islamabad who enjoys taking systems across boundaries—mobile, backend, ERP, and infrastructure—and turning the hard parts into reliable, repeatable processes. I work deeply in Android with Jetpack Compose, MVVM, and KMM, and I’ve also owned production features spanning iOS and Node.js backends, along with CI/CD and developer tooling.

Lately I’ve been focusing on AI-native engineering: designing gated, evidence-backed, agent-executable workflows that help teams move from raw client requirements to shipped tickets with clear acceptance criteria and safe release paths. At Xgrid.co, I’ve led high-risk ERP migrations and built SDLC pipelines and automation that reduced migration times dramatically while improving determinism, rollback safety, and engineering autonomy.

  • 4 years' experience
  • Joined September 2026

Languages

  • JavaneseAdvanced

Industry experience

  • Software & Internet
  • Computers & Electronics
  • Professional Services

Work experience

Senior Software Engineer · Xgrid.coSep 2022 – Present · 4 yrs 3 mos

Owned AI-native engineering workflows and developer tooling, including authoring a NAV → SQL strangler workflow to migrate ~200 ERP endpoints from Microsoft Dynamics NAV to a direct Sequelize/MSSQL backend. Implemented deterministic, rollback-safe execution with dual-service resolvers behind feature flags and automated value/type regression comparisons, cutting per-endpoint migration time from ~3 hours to ~30 minutes (~83%) and saving an estimated ~500 engineer-hours. Designed an agent-executable, org-wide SDLC pipeline with seven gated stages (intake to release) driven by evidence-backed pass conditions and intelligent failure loops, plus a stage/capability/engagement taxonomy to avoid duplicated logic across a shared skill library. Extended discovery into developer-ready tickets with traceable acceptance criteria, then integrated with the per-ticket pipeline at a defined seam.

Education

B.S. Computer Science · National University of Computer and Emerging Sciences (FAST-NUCES)2018 – 2022

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