• Problem: One codebase, many customers. Prevent data leaks, noisy neighbors, and runaway costs.
• What I do: Workspace isolation (RLS/tenant keys), per‑tenant quotas, env‑aware config, usage metering, cost dashboards.
• Results: Clean separation, fewer “who can see what” bugs, predictable infra bills.

• Problem: Monolith slowing teams, deploys risky, features blocked by cross‑team coupling.
• What I do: Slice by domain, establish contracts (gRPC/REST), async queues, idempotency, zero‑downtime rollout, observability.
• Results: Faster independent releases, blast radius reduced, clear ownership.

• Problem: High TTFB/LCP for international users; asset thrash; cache misses.
• What I do: Edge/CDN caching, signed URLs, ETags, image/video processing, prefetch/preload strategy, SSR/ISR hygiene.
• Results: Snappy UX worldwide with stable infra costs.

• Problem: Messy client events, duplicate IDs, broken funnels/cohorts.
• What I do: Typed SDKs, dedupe, backfill jobs, schema enforcement, replay protection, privacy filters, metric definitions.
• Results: Trustworthy dashboards that match reality.

• Problem: Teams spend cycles on boilerplate: CRUD, SDKs, API clients, DTOs.
• What I do: Code‑gen pipelines from OpenAPI/JSON Schema/Prisma; template kits; repo scaffolds.
• Results: Hours → minutes for new endpoints, consistent code, fewer bugs.

• Problem: Knowledge scattered in docs/calls; users need fast, accurate answers.
• What I do: RAG with chunking & eval, prompt routing, guardrails, vector stores, usage caps, latency budgets.
• Results: Helpful AI features that don’t hallucinate or surprise your bill.

• Problem: Remote research/meetings need recording, live notes, and searchable content.
• What I do: Zoom/Agora/VideoSDK integrations, STT → S3, speaker diarization, whiteboard, local/cloud recording.
• Results: Clear recordings, searchable insights, and reliable compliance.

• Problem: Extract structure from maps/scans and align to real‑world coordinates.
• What I do: CV/OCR pipelines, polygon extraction, WKT/GeoJSON export, Sentinel‑1/2 time‑series with xarray & GEE.
• Results: Usable datasets from messy imagery.

• Engineers at Meta (architecture reviews & performance deep‑dives).
• A Product Manager at Apple (research flows, UX acceptance criteria).
• A Director at Carter (roadmap, delivery, and KPI definition).

These are collaboration highlights; details kept confidential.

Frontend React · Next.js · Vite · Tailwind · shadcn/ui · Recharts/ApexCharts

Backend Node.js/Express · Python (Flask, Django) · Java/Spring Boot · REST/gRPC · WebSockets

Data & Storage MongoDB · Postgres/MySQL · Redis · S3 · Vector DBs

Infra & Perf CDN/Edge (CloudFront/NGINX) · Docker · PM2 · ffmpeg · CI/CD · Observability (logs/traces/metrics)

AI/LLMs OpenAI API · embeddings/RAG · prompt tooling · evaluation & guardrails

• Design for tenancy first. Isolation, quotas, and auditability are features.
• Measure before optimizing. Profiles, budgets, and SLIs/SLOs guide changes.
• Automate the boring parts. Code‑gen + templates keep teams shipping.
• Make it delightful. Fast UIs, accessible components, sane defaults.

Response time (p95/p99)

• Trim TTFB/LCP with edge caching & smart revalidation (SSR/ISR in Next.js), prefetch/preload, and route‑level data loaders.
• Eliminate N+1s & heavy joins; add covering indexes; paginate/stream results where payloads are large.
• Offload slow work with queues (BullMQ/Celery), write‑behind, and background fan‑out; keep APIs snappy.
• Reduce payload size: gzip/brotli, JSON streaming, image transformations, ETags/If‑None‑Match.
• Connection pooling, keep‑alive, TLS session reuse; stable p99s under load.
• Outcome: double‑digit reductions in p95/p99 and much faster time‑to‑interactive.

Cold start & throughput

• Warm pools/min replicas for serverless & containers; lazy‑init heavy SDKs; precompile templates.
• Backpressure and concurrency guards to keep queues healthy.
• Outcome: fewer latency spikes; steadier p99 under bursty traffic.

Reliability & correctness

• Timeouts, retries with jitter, circuit breakers, bulkheads.
• Idempotency keys & outbox pattern to prevent double writes.
• Strong contracts: versioned APIs, schema validation, and data migration playbooks.

Cost efficiency

• Cache‑first (Redis/edge) to cut DB load & egress; targeted TTLs and cache busting.
• Right‑size containers; autoscale on latency/QPS; job concurrency limits.
• S3 lifecycle policies; media compression (ffmpeg) and image CDNs.

Typical measurable deltas (context‑dependent, examples not guarantees)

• p95 latency: ↓ 30–60% after cache + query‑plan fixes.
• Cache hit ratio: ↑ +20–40 pp with refined edge rules & ETags.
• Egress: ↓ 25–50% via image/video optimization + CDN.
• Error rate: ↓ 40–70% after retries, idempotency, and circuit breakers.
• Infra cost: ↓ 15–35% through right‑sizing, autoscaling, and storage classes.

• Email: [email protected]
• LinkedIn: Zain Ansari