Apr 2024 – Present · 2 yrs 2 mos

• I head engineering for the Driver, Delivery, and Post-Order Customer Experience orgs at Swiggy, leading a highly skilled team of 100+ developers and SDETs. We work at the intersection of scale, speed, and complexity—solving tough problems across hyperlocal logistics, from order fulfillment, dynamic restaurant serviceability, and fleet efficiency to driver lifecycle management, payouts, and real-time delivery orchestration.
• My responsibilities also span post-order experiences, including intelligent service recovery, conversational AI/chatbots, customer contact center platforms, and location intelligence systems—all aimed at ensuring seamless interactions across our three-way marketplace of customers, restaurants, and delivery partners.
• Over the years, I’ve had the privilege of contributing to Swiggy’s remarkable scale journey, witnessing a 40x growth in order volumes and a 100x increase in traffic. I’ve led the creation of key platforms like the Location Platform and Workflow Platform, building critical infrastructure and capabilities from the ground up.
• A highlight has been nurturing an engineering culture that champions open source and innovation—from encouraging contributions to Netflix Conductor, to developing and open-sourcing our own functional testing framework, Grill.
• Collaboration is at the heart of everything we do—I work closely with product, data science, analytics, business operations, and program management teams to build scalable, intelligent, and impactful solutions that power Swiggy’s last-mile logistics engine.

Oct 2020 – Apr 2025 · 4 yrs 6 mos

• Leading the core logistics charter where my 40+ members teams are responsible for capacity allocation, driver assignment, batching, serviceability, promises and interfacing with 3PL logistics partners. These platforms are multi tenet in nature and cater to all business categories across Swiggy. These platforms drive the critical business customer, driver and cost per delivery metrics. These systems power and affect the entire journey of a customer’s order; from predicting SLAs for a given set of restaurants using AI models when the app is opened, to the time the order is delivered to the Customer’s doorstep. The team’s charter encompasses sophisticated algorithms and ML models that assign orders within minutes, in order to deliver the order within a 30-45min time slot, while maximising utilisation and efficiency of the fleet, to monitoring the order and automating interventions to handle exceptional conditions.

Jun 2017 – Oct 2020 · 3 yrs 4 mos

• Have donned several hats at Swiggy handling fulfilment, outbound call center operation, TnS, cancellation and location. Started my journey from breaking a legacy unstable monolithic into a set of highly scalable, resilient micro services architecture at the same time seeing a 15x growth. Was responsible for building an asynchronous workflow platform at Swiggy, forking Netflix Conductor, that is hosting 100+ workflows across Swiggy business lines at scale. In the process the team made open source contributions to the Netflix Conductor software.
• Built the multi tenet Location Platform from scratch to solve some of the hyperlocal location problems across Swiggy business lines related to accurate payout, address onboarding, enrichment and corrections, tracking screen experience, batching etc. As part of the Location Platform charter I was responsible for building various platforms under Routing, Central Address Service and Address Enrichment Jobs using DS models, Regions Core platform to power geo functions, Geofencing & Rider Movement Data ingestion pipeline.