# Supriya Guru

> Full Stack Software Engineer | Python, React, GraphQL, AWS | Building AI-Driven, Scalable & Secure Systems

Location: San Francisco, California, United States
Profile: https://flows.cv/supriya

Full Stack Software Engineer with 5+ years of experience building scalable, secure, and AI-powered applications across fintech and enterprise platforms. Skilled in Python (FastAPI, Django), React.js, and GraphQL, with hands-on expertise in real-time data pipelines (Kafka, PySpark, Redis Streams) and cloud-native architectures (AWS, Kubernetes, Docker, Terraform). I specialize in designing systems that combine strong backend engineering, modern frontends, and intelligent automation — improving performance, security, and reliability at scale.

Previously at Stripe and Meta, I built real-time analytics, fraud detection, and static analysis platforms that optimized financial reporting, reduced false positives, and strengthened application security. Passionate about data-driven development, observability, and continuous improvement, I enjoy collaborating on projects that blend AI, distributed systems, and modern web technologies to deliver measurable business impact.

## Work Experience
### Software Engineer - Full Stack Developer @ Stripe
Jan 2024 – Present
● Engineered real-time billing analytics platform with Python (FastAPI, Django REST), GraphQL (Ariadne), and Kafka Streams, delivering subscription insights with <15 min latency and <300ms query response times — increasing finance team reporting efficiency by 40%.
● Designed and exposed scalable APIs (REST + GraphQL), integrated with Stripe Radar APIs & Stripe Sigma, enabling fraud detection, reporting, and advanced customer analytics used by 10+ enterprise clients.
● Built front-end features with React.js + TypeScript, integrating dashboards and data visualizations for live subscription metrics and financial reconciliation.
● Orchestrated event-driven data pipelines using Kafka, Redis Streams, PySpark, and Celery to process millions of subscription updates with guaranteed delivery and retries — reduced processing failures by 75%.
● Optimized data storage and querying by leveraging PostgreSQL, MongoDB, Snowflake, AWS S3, and Apache Pinot, ensuring high availability for multi-tenant systems at scale and cutting query costs by 20%.
● Applied AI/ML techniques (Scikit-learn, PyTorch) to build anomaly detection and fraud risk scoring models on top of billing data streams, reducing false positives in fraud detection by 35% and improving chargeback prevention.
● Automated deployments using Docker, Kubernetes (EKS), Helm, and Terraform (IaC) with CI/CD pipelines (GitLab + GitHub Actions), achieving zero-downtime rollouts.
● Strengthened security & compliance by implementing OAuth2, JWT, RBAC, and ensuring adherence to PCI DSS and GDPR standards with encrypted storage and secure key management.
● Enhanced observability with Prometheus, Grafana, CloudWatch, ELK, and Datadog, reducing MTTR by 60% through proactive alerting and anomaly detection.
● Practiced Agile/Scrum (Jira) and collaborative DevOps culture, participating in sprint planning, peer code reviews, and authoring design documentation for cross-team knowledge sharing.

### Software Engineer @ Meta
Jan 2020 – Jan 2023
● Built security-focused full stack applications with Python (FastAPI, Django REST, Flask), GraphQL (Ariadne), React.js + TypeScript/Redux, enabling developers to visualize and triage static analysis findings in real time.
● Designed and optimized RESTful & GraphQL APIs with SQLAlchemy and PostgreSQL/MySQL, exposing taint-flow results to internal CI/CD pipelines and developer tools.
● Engineered scalable data-flow analysis modules using PySpark, Celery, and Kafka Streams, reducing analysis latency by 35% across millions of lines of Instagram’s Django/Python code.
● Integrated Redis / Redis Streams for caching and streaming intermediate results, improving throughput and reducing falsepositive detection rates.
● Applied AI/ML techniques (Python, Scikit-learn, PyTorch) to prioritize high-risk vulnerabilities and reduce noise, cutting false positives in static analysis alerts by 40%.
● Managed structured/unstructured storage with PostgreSQL, MongoDB, Snowflake, and AWS S3, ensuring compliance with PCI DSS, GDPR, AML, and sanctions verification standards.
● Containerized and deployed microservices with Docker, Kubernetes (EKS), Helm, and Terraform (IaC); automated build and release pipelines with GitLab CI/CD and GitHub Actions.
● Enhanced system security with OAuth2, JWT authentication, RBAC, and implemented end-to-end encryption and secrets management (AWS KMS) for compliance-critical workloads.
● Established observability and monitoring using CloudWatch, Prometheus, Grafana, and ELK, enabling proactive alerts and reducing incident response times by 60%.
● Implemented test automation with pytest, unittest.mock, Jest, and React Testing Library, increasing test coverage and ensuring reliability of both backend analyzers and frontend dashboards.
● Collaborated with cross-functional teams (PMs, data scientists, DevOps, QA) in an Agile/Scrum environment, delivering secure and scalable features with strong technical documentation (Swagger/OpenAPI, Postman).


## Education
### Masters in Computer Science
Montclair State University
Jan 2023 – Jan 2025

### Bachelor of Technology - BTech in Information Technology
Malla Reddy College of Engineering and Technology
Jan 2018 – Jan 2022


## Contact & Social
- LinkedIn: https://linkedin.com/in/supriya-guru-887369201

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Source: https://flows.cv/supriya
JSON Resume: https://flows.cv/supriya/resume.json
Last updated: 2026-03-22