Vignesh Elamvazhuthi

Senior Vice President of Engineering @Arcadia

San Francisco, CA, US
EMAILS
v••••••••@arcadia.io
MOBILE NUMBERS
+14•••••••52

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WORK HISTORY

Apr 2024 — Present

Senior Vice President of Engineering @Arcadia

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Lead a 130-person, multi-region organization that blends U.S. FTEs, nearshore teams in LATAM, and an offshore contractor network in Ukraine; unified R&D into a single delivery engine with clear ownership, career ladders, and high-signal performance practices.Platform modernization: evolved a monolith toward service-oriented systems and a governed analytics stack; standardized SDLC, CI/CD, and IaC so FTE and partner teams operate to the same quality bar.AI platformization: built shared capabilities (governed retrieval, prompt/policy libraries, offline/online evaluation, redaction/guardrails, human-in-the-loop, model monitoring) so squads can ship safely and iterate.Shipped multiple AI capabilities on the common platform—natural-language access to governed data and large-scale document understanding that powers semi-automated operational workflows—without one-off infrastructure.Release governance: release trains + hot-fix lane; feature-flagged, wave-based enablement (deploy!= release), safety gates, and practiced rollback playbooks.Cost & consistency: optimized the onshore/offshore/vendor mix, delivering seven-figure annual run-rate savings while improving delivery predictability.Enterprise readiness: contributed to SOC 2 Type II and ISO 27001 passes, with ongoing progress toward HITRUST alignment.

EDUCATION

2006 — 2008

Arizona State University

Master of Science, Computer Science

2002 — 2006

Https://Hindustanuniv.ac.in/

Bachelor of Engineering, Computer Science and Engineering

1999 — 2002

Naval Public School

High School

SKILLS

CArchitectureSqlLinuxC++UmlXmlSpringJavaEnterprise SoftwareDistributed SystemsSoftware Development

ABOUT VIGNESH ELAMVAZHUTHI

I lead engineering organizations that ship software customers can run every day—and trust.I’ve done it at Salesforce scale, in a ~40-person startup, and in a 300–400-person scale-up. Different stages, same bar: operability + outcomes. I adapt operating model, architecture, and leadership to the stage—without lowering the product standard: reliable in production, auditable when needed, and valuable enough that customers renew.I don’t ship prototypes or toys. I ship revenue products: secure, production-grade systems built for real-world usage, supportability, and continuous evolution.What that looks like in practice:• Outcome-driven product work with clear success measures (not feature checklists)• Production-first architecture: strong telemetry, SLOs/error budgets, healthy on-call, safe rollback, cost guardrails• Delivery systems that scale: intake → roadmap → release, release trains + an always-on hotfix lane, feature flags (deploy ≠ release), progressive rollout and preview-to-prod waves• Engineering fundamentals that compound: hiring/leveling, coaching, SDLC hygiene, incident learning loops, and crisp ownership boundaries across teamsI’m hands-on when it matters. Recently, I leaned heavily into AI-assisted development and strong upfront design to build and ship an MVP end-to-end—fast enough to unlock year-one value, and intentionally enough to become the foundation a team could scale on. AI compresses iteration time; engineering judgment ensures what ships is operable, maintainable, and secure.When AI is the right tool, I build the platform and governance for safe adoption: controlled data access and retrieval (RAG), evaluation (offline/online), monitoring, policy and privacy guardrails (including redaction/de-ID), and human-in-the-loop workflows—supporting enterprise trust programs (SOC 2 / ISO 27001 practices; progress toward HITRUST alignment).I enjoy partnering with Product, Security, Compliance, and GTM to turn PMF into a repeatable operating machine customers rely on.

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