R

Rajkishan Gunasekaran

Software Engineer

Bengaluru, Karnataka, India13 yrs 8 mos experience
Most Likely To SwitchHighly Stable

Key Highlights

  • 14+ years in building distributed systems.
  • Led privacy infrastructure transformation at Meta.
  • Expert in algorithmic trading and risk management.
Stackforce AI infers this person is a seasoned engineer specializing in Fintech and Social Media infrastructure.

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Skills

Core Skills

Privacy EngineeringInfrastructure DevelopmentPerformance MonitoringData AnalysisDeployment AutomationA/b TestingAnalyticsExperimentationAlgorithmic TradingInfrastructure OptimizationRisk ManagementReal-time ProcessingOptions PricingClient SolutionsData CompressionMobile DevelopmentModel Design

Other Skills

.NETAlgorithmsApache SparkCC#C++Cloud ComputingData MiningData StructuresDistributed SystemsHiveJavaJavaScriptLinuxMachine Learning

About

Engineer with 14+ years of experience building distributed, highly performant systems that solve complex problems at scale.

Experience

Meta

3 roles

Senior Staff Software Engineer

Jun 2025Present · 9 mos · On-site

Senior Staff Software Engineer

Promoted

Jun 2023Jun 2025 · 2 yrs · On-site

  • Privacy Infrastructure

Senior Staff Software Engineer

Oct 2015Sep 2022 · 6 yrs 11 mos · Menlo Park, California

  • As an engineering lead in the Privacy Products and Infrastructure org, I focused on Meta’s big bet to transform its infra to be privacy aware. Drove the technical direction and vision for developing frameworks that bake privacy deep within the company’s infra stack, allowing developers to
  • focus on building products while staying within the bounds of Meta’s global privacy commitments.
  • A Technical lead for the Application Performance Monitoring system at Meta, a
  • system synthesizes petabytes of telemetry data to produce actionable insights across 10k+ metrics,
  • detecting, diagnosing and preventing performance and reliability issues across Meta's family of apps including Facebook, WhatsApp and Instagram.
  • Technical lead for the automated canary analysis framework that Meta uses to safely and automatically
  • deploy a/b tests and configuration changes on mobile. Architected the system from the ground up,
  • partnering with teams across Config Infra, Mobile Perf and Data Science. The system executes the
  • safe and continuous delivery of tens of thousands of configuration changes and a/b tests everyday,
  • analyzing petabytes of performance telemetry data behind the scenes
  • Technical lead for the experimentation analytics platform that’s used across the company to understand the impact of A/B tests. Drove the roadmap and technical direction for several efforts in the experimentation space resulting in key wins across computation efficiency, availability
  • of actionable insights and overall decision quality.

Amazon web services (aws)

Principal Engineer

Sep 2022May 2023 · 8 mos · East Palo Alto, California, United States

  • EMR on EKS

Goldman sachs

Software Engineer

Jun 2012Sep 2015 · 3 yrs 3 mos · New York City Metropolitan Area

  • Worked on the Algorithmic Trading Platform used to run cash and options trading strategies across Equities. Made several improvements to the platform’s infrastructure including the event processing engine, real-time market data providers and the associated in-memory database and dataflow language.
  • Worked on the core risk engine used for generating realtime and end of day risk and PnL numbers across Equities. Focused on optimizing the scheduling, computation and pre-emption strategies used by the engine to improve the overall reliability and latency of the aggregate risk jobs.
  • Worked on Marquee - An application targeted at serving money managers, hedge funds and other clients of the firm. Developed the options pricing engine that allows clients to design options products with customized risk / returns.

Microsoft

Software Engineer Intern

May 2011Jul 2011 · 2 mos · Greater Bengaluru Area

  • Built an asymmetric data compression scheme for 3G mobile devices that helps save network bandwidth based on usage patterns. The scheme was implemented on Android and WP7 platforms and resulted in a 20% reduction in bandwidth consumption in an internal deployment study.

Technical university of munich

Research Intern

May 2010Jul 2010 · 2 mos

  • Designed analytical behavior models for different components of a plant and a constraint satisfaction framework that leverages these models to identify faulty components when fed with operation data.

Education

Indian Institute of Technology, Madras

Integrated Bachelors and Masters — Computer Science and Engineering

Jan 2007Jan 2012

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