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About
Capgemini engineer with 4+ years building and deploying high-availability, low-latency fraud detection APIs and multi-cluster distributed systems for a Fortune 20 bank, including zero-downtime production rollouts and multi-layer (SQL/network/hardware) performance debugging. Also built a Python + OpenAI/LangChain LLM-powered grading workflow for Austin School for Women, cutting feedback time from 90 minutes to 5 minutes per submission for 200+ learners.
Experience
Research Assistant (Data Processing & Insights)University of Texas at Austin
AI Development leadAustin School for the Driven
Lead Software Engineer (Associate Consultant)Capgemini
Senior Software EngineerCapgemini
Software EngineerCapgemini
Education
The University of Texas at Austin – McCombs School of Businessmaster, Information Technology & Management (2025)
SRM Universitybachelor, Information Technology (2021)
Key Strengths
Deployed multi-cluster fraud detection system handling billions of transactions annually with zero deployment downtime
Designed resilient production rollout strategy (blue-green, staged rollout, circuit breakers, rollback, health checks) for mission-critical payments
Full-stack troubleshooting across application/SQL, networking, and hardware; reduced incident resolution to ~3 days vs typical 2 weeks
Built real-time observability and shared Datadog dashboards to align cross-functional teams during deployments
Developed Python LLM-powered grading automation (OpenAI API + LangChain) for 200+ learners; cut feedback cycle from ~90 minutes to ~5 minutes and saved 7+ hours/week
Effective cross-functional coordination (daily syncs, war room, structured handoffs, escalation paths) that became standard operating procedure
Reference Highlights
Strongly Recommended
Strong ability to deploy and support complex production systems
Customer impact-first mindset during production issues
Strong debugging across software, hardware, and networks
Proactive testing that prevented downtime
Experience with high-scale transaction systems (billions annually; ~1M daily)
Effective in fast-changing customer environments
Good at aligning customer expectations with timelines and goals
Prioritizes work by impact and KPIs
Supportive teammate who helps others
Strong Python skills in production contexts
Resourceful problem-solver (researches and adapts when libraries/tools aren’t available)
Recognized/impressed client outcomes (received recognition at Capgemini)
Would be a strong “face of the team” in forward-deployed roles
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