Vetted AWS CodePipeline Professionals

“Built production LLM/RAG platforms for financial services to enable natural-language Q&A over large policy/compliance document sets stored in Snowflake and SharePoint. Strong in MLOps and orchestration (Airflow, ADF, Step Functions, MLflow) and in solving real production issues like stale embeddings and model performance, including an incremental Snowflake Streams sync that cut processing time from hours to minutes.”

“GenAI/LLM engineer who recently built a production compliance assistant at State Farm for KYC/AML and regulatory teams, using AWS Bedrock + LangChain with Textract/Lambda pipelines to extract fields, tag risk, and summarize long documents. Implemented RAG, strict structured outputs, and human-in-the-loop guardrails, and reports automating ~80% of documentation work while reducing review time by ~40%.”

“Full-stack engineer with ~3.5 years of Java Spring Boot and React experience who built an end-to-end banking transaction platform using microservices, Kafka streaming, AWS RDS, and Dockerized CI/CD. Demonstrates strong performance and reliability engineering (async processing, DLQ/retries, idempotency, caching) plus secure cloud deployment practices; has also worked across banking, healthcare, and insurance domains.”

“Data engineer with Charter Communications experience modernizing large-scale AWS data lake pipelines: ingesting S3 data, validating against legacy systems, transforming with PySpark/Spark SQL, and serving via Iceberg/Delta tables. Worked at 50M–300M record scale, delivered >99.5% data match, and built monitoring/alerting (CloudWatch/SNS) plus retry orchestration (Step Functions) and data quality gates (Great Expectations).”

“Full-stack engineer with hands-on production experience building real-time customer-facing features (order tracking + push notifications) across React/React Native and Node/Spring Boot with Postgres/MySQL. Demonstrates strong reliability patterns (transactional outbox, background workers, idempotent webhook ingestion) and has deployed/operated systems on AWS (ECS/Fargate/ALB, CloudWatch, CodePipeline) with structured observability and environment separation.”

Ramcharan SreenivasaReddy

Screened

Mid-level Full-Stack Developer specializing in FinTech platforms and cloud-native microservices

Texas, USA6y exp

“Backend/platform-focused Python engineer who has owned FastAPI services with Postgres/SQLAlchemy and production-grade auth (JWT + RBAC). Experienced deploying and operating microservices on Kubernetes with GitOps (ArgoCD), HPA tuning, and Prometheus/Grafana monitoring, plus hands-on cloud-to-on-prem migrations and Kafka-based real-time streaming pipelines.”

Shashank R

Screened

Senior Data Engineer specializing in cloud data platforms and real-time analytics

Las Vegas, NV6y exp

“Data engineer (Credit One) who built and owned real-time financial transaction and credit risk/fraud data systems end-to-end on AWS + Snowflake. Delivered high-scale pipelines (150k events/hour; ~2TB/week), raised data accuracy to 99%, and cut Snowflake costs 42% while adding strong observability, schema-drift handling, and production-grade APIs/documentation.”

“Infrastructure/Platform engineer with deep production ownership of large IBM Power/AIX estates (70 LPARs, dual VIOS, HMC across two data centers), including live DLPAR tuning and PowerHA clustering for Oracle/WebSphere. Also brings modern DevOps/IaC experience—built GitHub Actions pipelines deploying to Kubernetes with OIDC/Vault secrets and implemented Terraform to provision AWS EKS/VPC/IAM/ALB/RDS with drift detection and controlled rollouts.”