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Anshul Joshi
Mid-Level Software Engineer specializing in distributed systems and GenAI
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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.
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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
- 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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