Service Delivery Leader2020–2022120K annual hires, India
SQL QuickSight VBA Process Engineering
What Was Broken
A candidate applies, gets an offer, and then waits four months for a background check. Four months. In that time, they’ve probably accepted another offer, or lost interest, or both. The process was a chain of manual handoffs between vendors, Legal, and internal teams, with no single person able to see the full pipeline.
The 90th percentile was the real problem — most checks finished in 6–8 weeks, but the long tail of blocked cases dragged the average to four months.
The First Cut: Seeing the Board
Before we could fix the process, we had to measure it. SQL queries against the vendor databases, stitched together with VBA macros because nobody had built a real dashboard. The output went into QuickSight — color-coded by stage, flagged by delay, grouped by vendor.
What showed up was obvious once you could see it: three specific vendors were responsible for 60% of the delays. One of them had a broken API endpoint that nobody had reported because the fallback was manual email.
Rewriting the Rules
The fix wasn’t technical — it was procedural. We renegotiated SLAs with the two worst vendors, added an auto-escalation trigger at 30 days, and built a fallback path with a secondary vendor for the most common check types. The third vendor we just stopped using.
The verification workflows got re-engineered too. Instead of serial checks (A finishes, then B starts, then C), we parallelized everything that didn’t depend on the other. SQL tracked dependencies, QuickSight showed bottlenecks in real time, and the team stopped spending half their day chasing status updates by email.
Scaling the Team
Ten people couldn’t handle the volume at peak season, and four of them knew the whole process end-to-end. So we grew to 45 — not by hiring generalists, but by building specializations. One track for vendor management, one for exception handling, one for data quality. I mentored six of them into leads who now run their own teams.
The hardest part wasn’t the scaling — it was getting Legal and Compliance to agree that a 30-day SLA was actually safe. That took sitting in meetings, showing them the data, and earning trust that the new rules wouldn’t create risk.
The Numbers
90th percentile turnaround dropped from four months to one. Manual review time cut in half. The program touches 120K hires a year across India.
Most process problems aren’t engineering problems. You have to sit inside the process long enough to see where it actually breaks.
{"menu":[{"name":"Pages","items":[{"label":"Home","subtitle":"Overview","action":"navigate:/","icon":"page"},{"label":"Career","subtitle":"Timeline & principles","action":"navigate:/career","icon":"page"},{"label":"Projects","subtitle":"All projects","action":"navigate:/projects","icon":"page"},{"label":"About","subtitle":"About Meher","action":"navigate:/about","icon":"page"}]},{"name":"Settings","items":[{"label":"Toggle Theme","subtitle":"","action":"toggleTheme","icon":"theme"}]}],"fuse":{"threshold":0.6,"minMatchCharLength":2,"keys":["label","subtitle","searchableText"]},"projects":[{"title":"Global Payroll Platform","description":"In-house payroll platform across 6 APAC markets, $1.2B annually. I define the technical requirements, coordinate payments integrations, and make sure the engineering teams build what the business actually needs.","tags":["Python","SQL","API Integration","ISO 20022"],"link":"#","image":null,"techStack":["Python","SQL","API Integration","ISO 20022"],"size":"large","domain":"fintech","icon":null,"featured":true},{"title":"Fraud Detection Engine","description":"1.5M payment transactions analyzed. Built automated detection rules that caught the obvious cases — the ones that shouldn't need a human reviewing them. Cut manual validation by 80%. QuickSight dashboards so the non-technical teams could see what was flagged and why.","tags":["Python","QuickSight","Analytics"],"link":"#","image":null,"techStack":["Python","QuickSight","SQL"],"size":"medium","domain":"analytics","icon":null},{"title":"Background Check Revamp","description":"India's background checks were taking four months at the 90th percentile. Candidates would leave. Worked with Legal, Compliance, and Business to renegotiate vendor SLAs, parallelize the workflow, and grow the team from 10 to 45. Cut it to one month, impacted 120K annual hires.","tags":["Operations","Compliance","Process Engineering"],"link":"#","image":null,"techStack":["SQL","QuickSight","VBA"],"size":"medium","domain":"data","icon":null},{"title":"Sovereign Homelab","description":"50 services on bare metal: reverse proxy, DNS, VPN, password manager, photo library, media streaming, AI inference, git CI/CD, smart home, Matrix federation. Full observability via Grafana, Loki, Prometheus, and Alloy. No cloud provider.","tags":["Docker","Linux","Caddy","NetBird"],"link":"#","image":null,"techStack":["Docker","Caddy","NetBird","Vaultwarden"],"size":"large","domain":"infrastructure","icon":null,"featured":true},{"title":"AI Node","description":"Private LLM inference on CUDA GPU. llama.cpp server with quantized models, Open WebUI frontend. Used through OpenCode on my laptop and my Hermes agent on Matrix when I'm out. No cloud APIs, no telemetry.","tags":["CUDA","llama.cpp","Open WebUI"],"link":"#","image":null,"techStack":["Python","CUDA","llama.cpp"],"size":"medium","domain":"ai","icon":null,"featured":true},{"title":"AI & LLM on Your Homelab — A Tutorial","description":"Step-by-step guide to running your own AI inference stack at home. llama.cpp, Open WebUI, Caddy reverse proxy, Matrix integration — everything local, everything yours.","tags":["Tutorial","AI","llama.cpp","Homelab"],"link":"#","image":null,"techStack":["llama.cpp","Open WebUI","Caddy","Docker"],"size":"medium","domain":"ai","icon":null,"featured":false},{"title":"Matrix Citadel","description":"Self-hosted Matrix federation with full voice and video via dual LiveKit servers. Twunnel bridges between two homeservers, JWT auth services, OpenClaw Gateway for AI agent orchestration.","tags":["Matrix","LiveKit","Twunnel"],"link":"https://cloudcitadel.in","image":null,"techStack":["Matrix","LiveKit","Twunnel","OpenClaw"],"size":"medium","domain":"infrastructure","icon":null},{"title":"Media & Photo Stack","description":"Jellyfin streaming with automated library management, subtitles, and analytics. Immich photo library with ML-powered face recognition and reverse image search.","tags":["Jellyfin","Immich","Media Server"],"link":"#","image":null,"techStack":["Jellyfin","Immich","PostgreSQL"],"size":"medium","domain":"infrastructure","icon":null},{"title":"Observability Stack","description":"Full infrastructure telemetry: Grafana dashboards, Loki log aggregation, Prometheus metrics, Alloy collector, plus node, process, and disk health exporters. Monitoring 50 services and bare-metal health in real time.","tags":["Grafana","Prometheus","Loki","Alloy"],"link":"#","image":null,"techStack":["Grafana","Prometheus","Loki","Alloy"],"size":"medium","domain":"infrastructure","icon":null},{"title":"Gitea","description":"Self-hosted git server with CI runner and built-in container registry. This is where the folio lives — code pushed here, the runner builds it, the registry stores the image, and it deploys back to the same machine. Source to production, nothing leaves the box.","tags":["Git","CI/CD","Container Registry"],"link":"https://git.nexusno.de","image":null,"techStack":["Gitea","Docker","CI/CD"],"size":"medium","domain":"infrastructure","icon":null},{"title":"Immich","description":"Photo library with ML-powered face recognition, reverse image search, and automatic duplicate detection. Replaces Google Photos without the telemetry — all the smart features, none of the cloud.","tags":["Immich","ML","Photos"],"link":"#","image":null,"techStack":["Immich","OpenVINO","PostgreSQL"],"size":"medium","domain":"infrastructure","icon":null},{"title":"Home Assistant + Frigate","description":"Smart home automation with AI security camera system. Frigate does hardware-accelerated object detection — people, dogs, cars — on the cameras, not the cloud. Home Assistant ties everything together: lights, sensors, automations, and camera events.","tags":["Home Assistant","Frigate","Smart Home"],"link":"#","image":null,"techStack":["Home Assistant","Frigate","Docker"],"size":"medium","domain":"infrastructure","icon":null},{"title":"SearXNG","description":"Self-hosted metasearch that aggregates results from Bing, Wikipedia, and others without tracking. Replaces the browser search bar — same results, no data broker on the other end.","tags":["SearXNG","Privacy","Search"],"link":"https://search.nexusno.de","image":null,"techStack":["SearXNG","Docker","Valkey"],"size":"small","domain":"infrastructure","icon":null}],"skills":{"tools":["Python","SQL","QuickSight","VBA","Docker","Linux","Kubernetes","Grafana","Prometheus","Loki","Caddy","Matrix"],"standards":["ISO 20022"],"domains":["Payments","Infrastructure","Process Engineering"]},"contact":{"email":"hi@meherchaitanya.com","channels":[{"label":"Email","url":"mailto:hi@meherchaitanya.com","displayText":"hi@meherchaitanya.com","icon":"mail","external":false},{"label":"LinkedIn","url":"https://linkedin.com/in/meherchaitanya","displayText":"meherchaitanya","icon":"linkedin","external":true},{"label":"Matrix","url":"https://matrix.to/#/@meher:hanumara.online","displayText":"@meher:hanumara.online","icon":"matrix","external":true}]}}