LIVE NOW: Building Dynamic Ads at Meta · San Francisco · open to chat EST. 2014

Career · 2014 → now

Meta '24 → now Stellar Foundation '23 – '24 Robinhood '21 – '22 Dropbox '19 – '21 Quantstamp YC W18 '17 – '18 Barclays '15 – '17

Shipped · by the numbers

$7M+
annualized iRev
Meta · frequency capping
−48%
RPC latency
Stellar Platform
30+
product flows orchestrated
Robinhood · SMaaS

Featured · now

Frequency Capping Platform · Meta Ads

Policy-driven, low-latency capping for Dynamic Ads. Combines onsite engagement with offsite conversions via batch and near-real-time streaming. Integrated into the final-stage Ads ranking stack without impacting serving SLAs. $7M+ iRev delivered →

Also built

LLM Ads-debug agent

Internal AI agent using RAG over logs/metrics + tool use to cut root-cause time for Ads delivery issues.

State Machine as a Service

JSON-configured workflow engine at Robinhood. 30+ flows; new launches 3–5× faster.

Stellar RPC service

Re-engineered transactions/events handling with optimized caching. Core endpoint latency down 48%.

Dropbox Spaces

Led 4-engineer team building core collaboration features: notifications, membership, workspace creation.

Full experience

Oct 2024 → now

Meta

Senior Software Engineer · Dynamic Ads

  • Led architecture and development of a scalable frequency capping platform for Dynamic Ads within Meta's Ads recommendation stack, combining onsite engagement with offsite conversions via batch and near-real-time streaming pipelines.
  • Built a generic, policy-driven framework supporting per-user, per-ad, and per-campaign caps with dynamic tuning based on objective, cohorts, and signal quality.
  • Integrated capping into the final-stage Dynamic Ads recommendation stack as a low-latency ranking and delivery-control feature without impacting serving SLAs.
  • Delivered $7M+ annualized iRev by reducing inefficient repeat exposure and improving delivery quality.
  • Built an internal LLM-powered AI agent for Ads debugging — retrieval over logs/metrics, prompt orchestration, and tool use to accelerate root-cause analysis.
Jun 2023 → Oct 2024

Stellar Development Foundation

Senior Software Engineer

  • Architected and developed a new backend system for handling transactions and events in the Stellar RPC service.
  • Re-engineered the RPC service with optimized caching in Stellar Platform — core endpoint latency down 48%.
  • Led platform and SDK releases for enterprise deployments and global developer adoption across the Stellar ecosystem.
Nov 2021 → Oct 2022

Robinhood

Senior Software Engineer

  • Architected and implemented a State Machine as a Service platform (Python, Go, Redis, PostgreSQL, AWS) — engineers deploy complex product flows via JSON in ~10 minutes instead of multi-week custom builds.
  • Built the core execution engine, transition framework, caching layer, and durable state store for UI-driven workflows with backend DB/RPC side effects — cutting duplicated product-flow engineering by ~42%.
  • Drove adoption across 30+ product flows — crypto asset launches, onboarding, eligibility checks, multi-step transaction experiences — accelerating new product launches 3–5×.
Jun 2019 → Nov 2021

Dropbox

Software Engineer · Dropbox Spaces

  • Designed and built core collaboration features for Dropbox Spaces, a project-centric virtual workspace for teams (Go, Python, Protobuf, gRPC).
  • Led a 4-engineer team through design reviews, sprint planning, on-call, and cross-functional execution across notifications, membership management, and workspace creation.
  • Developed backend services and APIs integrating with Dropbox identity, sharing, and collaboration systems.
Jul 2017 → Aug 2018

Quantstamp · YC W18

Founding Software Engineer

  • First engineer on the web product team — built the MVP from scratch.
  • Worked directly with the CEO and CTO to build an asynchronous backend so customers could receive audit reports without blocking on submission.
Mar 2015 → Jul 2017

Barclays

Senior Software Engineer · Payments / Fraud / Collections

  • Developed modules in Payment, Fraud, and Collection services handling millions of user requests daily (Java, Spring, AWS).
  • Optimized the transaction/payment validation pipeline — 30% latency reduction via async processing and batch handling.
  • Collaborated with the data science team on fraud detection models — +25% detection accuracy.
  • Implemented rule-based decision engines to prioritize collection efforts by customer profile and payment history.

What people I've worked with say

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