Python Full-Stack Developer for AI/ML Systems

RAJKUMAR VELPULA

Python Full Stack Developer

New York Open for relocation to Seattle, WA Dallas, TX Chicago, IL San Francisco, CA *****************@*****.*** 314-***-**** linkedin.com/in/rajkumarvelpula/ SUMMARY

Experienced Python Developer with 5+ years of expertise in Python 3.x, OOP, Pandas, NumPy, SQL (PostgreSQL, Oracle, MS SQL), and PySpark, delivering scalable data pipelines, AI/ML models, and cloud-native microservices for Stripe, PayPal, and Accenture. Skilled in FastAPI/Django REST, Kafka, ETL/ELT workflows, and real-time streaming systems on AWS (S3, Lambda, ECS/EKS, Glue, Redshift) and Azure. Proven record reducing latency, improving personalization, and ensuring PCI-DSS compliance and auditability across high-throughput platforms. Certified in AWS Data Engineering, PCAP Python, and Azure Data, with strong DevOps skills in Docker, Kubernetes, Terraform, and CI/CD (GitHub Actions, Jenkins, Pytest). PROFESSIONAL EXPERIENCE

Stripe Jan 2025 - Present

Python Developer New York, NY

Increased real-time content personalization accuracy by 37% by building Python-based ML microservices on Shepherd, boosting user engagement and retention across Stripe’s merchant ecosystem.

Accelerated ad-monetization revenue by 22% through the creation of scalable data ingestion pipelines that processed 10TB/day of user interaction data for targeted campaign delivery and ROI optimization.

Reduced payment transaction latency by 40% by refactoring legacy Python services into asynchronous FastAPI-based architectures, enabling low-latency checkout experiences across streaming media surfaces.

Developed high-performance AI inference pipelines using Python, TensorFlow, and PyTorch to deliver real-time model scoring for content and ad personalization.

Engineered event-driven microservices with FastAPI, gRPC, and Kafka, enabling sub-100ms message propagation across the Shepherd ML orchestration layer.

Implemented ETL/ELT data workflows using Apache Airflow, PySpark, AWS Lambda, S3, and Redshift, automating large- scale pipelines that powered real-time media analytics dashboards.

Designed streaming media delivery backends using FFmpeg, WebRTC, and Redis caches integrated with Python services for adaptive bitrate content delivery.

Integrated Stripe Payments APIs and GraphQL gateways into Shepherd services to support real-time ad billing, subscription handling, and cross-border currency settlements.

Deployed infrastructure using Terraform, Docker, and Kubernetes to achieve horizontally scalable ML clusters with auto- healing and zero-downtime rollouts.

Built feature stores and vector databases with Feast, Pinecone, and PostgreSQL to power personalized recommendations and user behavior prediction models.

PayPal Feb 2024 - Jan 2025

Software Engineer New York, NY

Developed high-throughput Python microservices for PayPal’s wallet engine, cutting API latency by 37% and boosting transaction completion rates by 22% across global markets.

Integrated ML-driven fraud detection pipelines into payment workflows, boosting fraud prevention accuracy to 98% while cutting false positives by 30%, directly improving merchant trust and user retention.

Engineered AI-based subscription retention models using Python and PyTorch, recovering $15M+ in recurring revenue annually by proactively preventing churn from failed renewals.

Designed and deployed scalable backend services using Python (FastAPI, Django REST), gRPC, and GraphQL to handle millions of payment and wallet API calls daily.

Built real-time Kafka-based streaming pipelines for transaction event ingestion, enabling millisecond-level payment reconciliation and ledger synchronization.

Developed containerized microservices using Docker, Kubernetes (EKS), and Helm, ensuring zero-downtime deployments and rapid global scaling of wallet services.

Built CI/CD pipelines (GitHub Actions, Jenkins) with automated tests (Pytest), type checks (mypy), and security scans

(bandit, SonarQube), ensuring PCI-DSS compliance, audit readiness, and code quality.

Implemented cloud-native architecture leveraging AWS (Lambda, S3, DynamoDB, CloudFront)and Infrastructure as Code

(Terraform) to support elastic scaling of payment workloads.

Built and served real-time AI personalization models with TensorFlow, MLflow, and Redis, delivering dynamic checkout recommendations and improving conversion rates by double digits Accenture July 2020 – July 2023

Python Developer India

Spearheaded development of AI-driven incident detection pipelines that reduced mean-time-to-resolution (MTTR) by 43% and cut manual ticket triage by 60%, accelerating operational efficiency across 10K+ engineering nodes globally.

Engineered real-time telemetry pipelines and FastAPI microservices using Python (AWS Lambda, Azure Functions), enabling 200ms anomaly detection and seamless integration with ServiceNow and Splunk for proactive service recovery.

Built scalable AI/ML personalization models using TensorFlow, PyTorch, and scikit-learn, served via Python REST endpoints to dynamically prioritize alerts and recommend remediation actions.

Implemented data pipelines with Apache Airflow, Kafka, and asyncio-based Python stream processors to handle continuous operational telemetry and trigger real-time alerts.

Developed cloud-native automation scripts with boto3, azure-mgmt, Docker, and Kubernetes on Linux/Unix, enabling zero- downtime rollouts, horizontal scaling, and compliance with enterprise audit controls.

Established robust observability and tracing using OpenTelemetry, Prometheus Python exporters, and structured logging

(loguru) to ensure full-stack monitoring, auditability, and performance tuning. TECHNICAL SKILLS

Programming Languages: Python (OOP, AsyncIO, Multiprocessing, automation, ML modeling, microservices), SQL (PostgreSQL, Oracle, MS SQL, advanced querying & optimization), PySpark, R, Scala, C++, Java, Bash, Go, C Machine Learning & AI: TensorFlow, PyTorch, scikit-learn, MLflow, Pandas, NumPy, SciPy, feature stores (Feast, Pinecone), NLP

(spaCy, Transformers), AI personalization, predictive modeling, LLM integration (LangChain, RAG, vector DBs: FAISS/PGVector) Data Engineering & Streaming: Apache Kafka, Apache Airflow, PySpark, Hadoop, Hive, dbt, asyncio, ETL/ELT pipelines, Redis, S3, DynamoDB, PostgreSQL, data lake/warehouse architecture (Redshift, Snowflake) Cloud & DevOps: AWS (Lambda, S3, ECS/EKS, Glue, EMR, Redshift, API Gateway, SQS/SNS, CloudFront), Azure Functions, Terraform, CloudFormation/CDK, Docker, Kubernetes, Helm, CI/CD (GitHub Actions, Jenkins), SonarQube, Fortify Backend & Microservices: FastAPI, Django REST, Flask, gRPC, GraphQL, REST APIs, event-driven architecture, WebRTC, FFmpeg, real-time system design

Payments & AdTech Systems: Stripe API, PayPal API, subscription management, fraud detection, ad monetization, real-time billing pipelines, PCI-DSS compliance, Basel/audit automation Testing & Quality Assurance: Pytest, Behave, Unit/Integration/E2E testing, mypy (type validation), bandit (security linting), automated test pipelines

Observability & Monitoring: OpenTelemetry, Prometheus, structured logging (loguru), performance tuning, anomaly detection, full-stack observability

EDUCATION

Master’s in Business Analytics

Webster University

CERTIFICATION

AWS Certified Data Engineer - Associate

PCAP - Certified Associate in Python Programming

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