Led engineering for the Safety Cameras Team, owning technical execution, architecture, and mentorship; partnered with Staff PM, Embedded, IoT, and Design. Served as STO, driving sprint planning, performance reviews, and end‑to‑end delivery.

• Developed and deployed real‑time distributed IoT pipelines on Kubernetes using Kafka, gRPC, Go, and AWS IoT Core—optimizing for millisecond latency, horizontal scalability, and 99.9% reliability.

• Played a key role in building a next‑gen vehicle gateway with camera systems, including an MQTT metadata pipeline for multi‑resolution video requests.

• • Deployed real‑time speeding detection and in‑cab alerts, reducing high‑risk driving behavior by 75%.

• • Automated IoT device fault detection and quarantine via Datadog, Statsig; designed telemetry pipelines to track system health and proactively prevent service degradation.

• Led API optimization—indexing, partitioning, caching, async processing, and deprecating low‑value metrics based on Pendo insights—cutting latency by up to 80%.

• Modernized the event‑filtering engine, reducing processing costs by 30% and enabling fleet‑specific configurability.

• Designed a rule‑based severity model for speeding events, enabling targeted driver coaching and reducing repeat high‑risk offenses by 25%.

• Contributed to org‑wide architectural standards, defining scalability and reliability patterns for real‑time IoT streaming.

• Mentored engineers through code reviews, architecture deep dives, and 1:1 coaching; influenced biannual roadmaps and feature prioritization with data‑driven system performance analyses.

• Led on‑call rotations and incident management, establishing observability best practices and custom dashboards in Datadog.

• Interviewed 50+ candidates, scaling high‑bar hiring across backend, infrastructure, and system design.

Tech Stack: Go, Ruby on Rails, Python, Kafka, Kubernetes, gRPC, AWS services, PostgreSQL, Redis, DynamoDB, Terraform, Datadog, Statsig

• Designed and delivered event-driven microservices for IoT Smart Fridges, achieving 99.9% uptime and directly supporting core product and revenue growth through resilient infrastructure.

• Led migration from monolithic REST API to GraphQL, cutting data over-fetching and response times by 35% resulting in a faster, more personalized user experience.

• Built robust CI/CD pipelines with automated testing and rollback, reducing deployment time by 60% while sustaining 85%+ test coverage and increasing release confidence.

• Delivered revenue-driving features—including mobile ordering, subscriptions, loyalty, and referrals—resulting in a 25% increase in transactions and a 30% revenue lift.

• Built scalable in-app notifications and SMS platforms, enabling new customer engagement strategies and enhancing cross-channel communication for growth marketing.

• Developed anomaly detection for inventory, delivery, and fridge temperature, reducing downtime risk and preventing operational losses through real-time alerting and monitoring.

• Implemented passwordless authentication with Amazon Cognito, boosting mobile engagement by 15% while enhancing security and simplifying the login experience.

• Optimized third-party integrations (Twilio, Segment, Slack), streamlining workflows across customer support and ops teams to improve efficiency and response times.

• Mentored junior and mid-level engineers while driving best practices in scalable system design and agile delivery, ensuring alignment between engineering quality and product velocity.

• Helped scale engineering team - hiring, onboarding, and coaching to build strong, high-performing talent.

• Improved IoT device battery life by 40% by implementing bulk data update features in ThingSpeak.

• Developed internal API monitoring tools and won the Intern Hackathon with an IoT-based parking solution.

For Cadillac

• Developed 'Favorites' feature and customized Android HMI layouts for Cadillac infotainment displays, improving UX consistency and usability.