Greater Boston
Own a self-hosted SaaS suite end-to-end — architecture, code, infrastructure, and production ops across Python/Django & Flask apps with integrated AI. • CRM & Ticketing (Django 5): Built a greenfield ticketing/CRM with shared Gmail/OAuth intake, threaded replies, internal/external comments, merge/split workflows, role-based access, and dynamic fields. Added a pgvector RAG knowledge base that injects product/FAQ context into LLM-generated replies. Postgres, Celery, Redis, HTMX. • E-Signature App (Django): Built a Docusign-style e-sign product — Jinja field-token templates, an HTML→PDF pipeline (WeasyPrint/pyhanko/reportlab), secure public signing links, and a REST API + webhooks for CRM integration. • SEO Reporting Platform (Django): Self-service Search Console + GA4 reporting with run-over-run comparisons and a Celery Beat onboarding lifecycle (approvals, reminder emails, deadlines). Deployed on Kubernetes. • Marketing Sites (Flask): SEO-optimized, server-rendered sites with schema.org data, programmatic location pages, and an automated responsive-image pipeline in the Docker build. • Infrastructure: Designed and operate the ingress for the whole suite — Caddy TLS termination over hardened reverse-SSH tunnels, Dockerized gunicorn stacks, scripted deploys. • AI Tooling: Authored reusable Claude Code skills — a 250+ check multi-platform ad-audit engine, a Gemini image-generation tool, and a Playwright-based site-modernization tool. Skills: Python · Django · Flask · PostgreSQL · pgvector · Redis · Celery · RAG/LLM integration · Google APIs · OAuth · Docker · Kubernetes · Caddy · CI/CD ·Playwright
High Touch Support (HTS) – Elite VVIP Team (2022 – Present) Serve as the primary reliability lead for Google’s most strategic global accounts, proactively reducing escalations by 25% through architectural deep-dives and infrastructure audits. Incident Command: Lead response for large-scale production outages with executive visibility; coordinate across cross-functional engineering teams to drive rapid resolution and post-mortem analysis. Toil Reduction: Design and deploy automated tooling in Python and Go to accelerate alerting and troubleshooting, reducing mean-time-to-detection (MTTD) for critical incidents. Subject Matter Expert (SME) – Compute Engine (GCE) (2017 – 2022) System Design & Talent: Conducted 250+ technical interviews focused on system design and software development; standardized hiring rubrics for the TSE organization. Knowledge Engineering: Authored an extensive internal and external technical knowledge base, measurably reducing support volume by empowering customer self-service. Global Scaling: Spearheaded the technical onboarding for founding TSE teams in NYC and Austin, ensuring operational readiness and consistent engineering standards across new sites. Mentorship: Trained 500+ new hires through the "Life of a TSE" simulation, focusing on root cause analysis (RCA) and complex system debugging.
Infrastructure Scaling: Redesigned a core legacy system to increase throughput from 100k requests/month to 6 billion requests/month, ensuring 99.9% availability during rapid growth. Performance Optimization: Architected a video serving and transcoding system for an ad server, reducing latency from 2s to <200ms. Reliability Standards: Established the team’s first formal Code Review and automated testing protocols (CI/CD), significantly reducing production regressions
Infrastructure Scaling: Redesigned a core legacy system to increase throughput from 100k requests/month to 6 billion requests/month, ensuring 99.9% availability during rapid growth. Performance Optimization: Architected a video serving and transcoding system for an ad server, reducing latency from 2s to <200ms. Reliability Standards: Established the team’s first formal Code Review and automated testing protocols (CI/CD), significantly reducing production regressions.