Vetted Amazon CloudWatch Professionals

“QA tester with end-to-end ownership of feature/module quality across the full development lifecycle (kickoff through release validation), using Jira/TestRail and disciplined triage workflows. Cites catching a critical data mismatch before release and a reproducible HUD/UI update defect supported by video and system logs; has not yet shipped a AAA title but has comparable production QA processes.”

“Built and scaled a multi-agent LLM automation pipeline during a fintech internship, growing from a rapid 1-week proof-of-concept to a 15+ agent hierarchical system that cut market brief report generation time from ~5 hours to under 30 minutes. Hands-on with agent frameworks (Haystack, CrewAI, LangChain) and experienced in debugging agent communication issues via sandboxed modular testing and context/token management; also regularly gives architecture-first technical demos at multiple hackathons and university events.”

“Infrastructure/DevOps engineer (Vidmob) focused on AWS + containers, owning GitLab CI/CD and Terraform-managed environments. Led a high-impact CI incident by correlating runner queue time, Docker pull latency, and NAT egress; implemented ECR pull-through caching and VPC endpoints to restore performance and then standardized the fix in Terraform for future scale-ups.”

“Built and deployed a production compliance automation RAG system (at Citi) that generates citation-backed, schema-validated risk summaries for regulatory document review. Emphasizes regulated-environment reliability with retrieval-only grounding, abstention, confidence thresholds, and immutable audit logging, plus orchestration using LangChain/LangGraph and Airflow. Reported ~60% reduction in compliance review effort while maintaining high precision and traceability.”

“Backend/platform engineer with production ownership of high-volume transaction analytics and fraud monitoring services built in Java/Spring Boot. Has scaled data processing platforms (including healthcare datasets) and operated Kafka-based event pipelines with schema versioning, deduplication, and replay/backfill workflows, using strong observability via CloudWatch/Grafana and CI/CD with Jenkins.”

“Backend/platform engineer who has owned end-to-end production systems in financial/claims domains, including a transaction analytics microservice platform processing ~10M daily operations and cutting latency from ~150ms to <70ms. Also productionized an LLM-powered monitoring/alerting capability (Llama 3 + FastAPI) with prompt design, guardrails, and production evaluation, and led monolith-to-microservices modernization on AWS using feature flags and parallel runs.”

“Built a production internal LLM-powered knowledge assistant using a RAG architecture (Python, LLM APIs, cloud services) that answers employee questions with sourced, grounded responses from internal documents. Demonstrates strong practical depth in retrieval tuning (chunking/metadata filters), orchestration with LangChain, and production reliability practices (latency optimization, automated embedding refresh, evaluation metrics, logging/monitoring) while partnering closely with non-technical operations teams.”

“Software engineer with hands-on ownership of both fintech checkout improvements (saved payment methods/one-click checkout with tokenization and feature-flag rollouts) and production LLM/RAG systems for customer support. Demonstrates strong operational rigor via guardrails, evaluation loops integrated into CI/CD, and scalable data pipelines handling messy PDFs/CSVs/logs with reliability and observability.”

“Data engineer (Charles Schwab) who took ownership of an unstable, ambiguous nightly financial data pipeline and rebuilt it into a reliable, incremental AWS Glue/Airflow/Redshift system feeding Power BI. Created a custom Python data-quality framework with hard-stop gating and schema drift detection, improving integrity (99.9%), cutting runtime (~20%), and reducing incidents/tickets (35% fewer schema-related dashboard incidents; 30% fewer investigations).”

Goutami Amara

Screened

Mid-level Full-Stack Java Developer specializing in FinTech and Healthcare platforms

Memphis, TN6y exp

“Software engineer who built internal operations/monitoring dashboards for real-time trading and money-movement systems, emphasizing auditability and rapid iteration. Deep experience with microservices on Azure using Kafka/RabbitMQ, plus strong testing discipline (JUnit/Mockito/Testcontainers, contract/E2E) and observability patterns (correlation IDs, centralized logging, distributed tracing) to reduce incident triage time and improve resilience.”

Sai Harshith Tanguturi

Screened

Mid-Level Software Engineer specializing in Java microservices and AWS cloud-native systems

Grapevine, TX3y exp

“Full-stack engineer who has owned customer-critical analytics and course intelligence platforms end-to-end (React/TypeScript + Node/Express + SQL), including an internal self-serve Reporting & Analytics Center adopted by 1,000+ users. Demonstrates strong systems thinking across performance (2× faster heavy reports), reliability (feature flags, testing), and distributed architecture (RabbitMQ microservices with idempotency, DLQs, and correlation-ID observability).”

Sai Vamsi

Screened

Mid-Level Software Engineer specializing in backend microservices and cloud-native systems

TX, USA4y exp

“ServiceNow engineer who built an AI-powered ticket summarizer end-to-end (RAG with vector DB + GPT, Redis latency optimizations, fallback summarization, and a React UI widget for agent feedback). Also has hands-on ROS 2 experience building real-time sensor-fusion nodes (LiDAR/IMU), debugging SLAM/navigation issues via rosbag + EKF tuning, and bridging heterogeneous robots by translating ROS 2 topics to MQTT/JSON. Strong DevOps background with Docker, Jenkins CI/CD, and Kubernetes orchestration for scalable deployments.”

Yashwanth Naidu

Screened

Mid-level Full-Stack Developer specializing in cloud-native Java/React microservices

USA4y exp

“Backend/DevOps-focused engineer with hands-on ownership of Java Spring Boot microservices on AWS, including Kubernetes deployments, Jenkins-based CI/CD, and GitOps-driven infrastructure-as-code (Terraform/Helm). Delivered measurable performance gains (25% faster APIs) and built a Kafka real-time streaming pipeline with strong observability (Prometheus/Grafana/CloudWatch) and rapid rollback practices that cut production downtime from hours to minutes.”

Jhansi D

Screened

Senior Full-Stack Java Developer specializing in cloud-native microservices

Chicago, Illinois4y exp

“Full-stack engineer with experience building secure, cloud-native document/workflow platforms handling high-volume customer and medical data across microservices on Kubernetes. Demonstrated impact improving performance via event-driven AWS architectures (Lambda + DynamoDB Streams) and strengthening compliance/security for S3-stored documents using IAM and KMS. Has delivered end-to-end APIs and UIs using Java/Spring Boot with Angular/React, plus Docker and CI/CD.”

Uday kumar swamy

Screened

Senior Machine Learning Engineer specializing in MLOps and NLP/GenAI

Chicago, USA9y exp

“Built a production LLM-agent framework for a startup that performs daily financial/trading analysis by combining live market data with internal tools, including a centralized memory module to prevent context drift and reduce hallucinations. Also implemented an Airflow-orchestrated retail price forecasting pipeline deployed to AWS endpoints, scaling parallel workloads via Kubernetes Executor and validating systems with rigorous functional + LLM-specific metrics and cross-team collaboration.”

Binaal Bopanna

Screened

Mid-level Solutions Engineer specializing in AI automation and hybrid cloud infrastructure

USA4y exp

“Built and productionized AI-driven insurance claims document intelligence/automation at American Family Insurance, integrating OCR/NLP models and a rules-based validation layer into existing claims systems via APIs. Delivered measurable impact (≈28% accuracy lift, ≈35% reduction in manual processing time) and modernized legacy workflows with phased cloud migration, feature flags, parallel runs, and CloudWatch-based monitoring.”

UMESH KAMISETTY

Screened

Mid-level Data Engineer specializing in cloud lakehouse and streaming platforms

Seattle, WA5y exp

“Data engineer focused on building production-grade pipelines on AWS (Kafka/Kinesis/Glue/S3) through to curated serving layers in Snowflake and Delta Lake. Emphasizes automated data quality validation (PySpark + CI/CD), modular dbt transformations for analytics (customer spending, risk metrics), and operational reliability with CloudWatch and DLQs; data consumed by BI tools and ML pipelines for fraud detection and risk analytics.”

Harshitha Parupalli

Screened

Mid-level Data Engineer specializing in multi-cloud real-time and batch data pipelines

Jersey City, NJ4y exp

“Data engineer with healthcare domain experience who owned 100M+ record pipelines end-to-end (Kafka/Kinesis/ADF → PySpark/dbt validation → Spark SQL transforms → Snowflake/Power BI serving). Built production-grade reliability practices (Airflow orchestration, CloudWatch/Grafana monitoring, pytest + contract/regression tests, idempotent ingestion/backfills) and delivered measurable improvements: 35% lower latency and 40% better query performance.”

SAITEJA MALLEMPUDI

Screened

Senior Data Scientist and AI/ML Engineer specializing in GenAI and cloud ML

Chicago, IL6y exp

“ML/AI engineer with hands-on experience owning systems from experimentation through deployment and monitoring, including a Bank of Montreal project that improved timely interventions by 12%. Also brings GenAI/RAG experience with evaluation and safety guardrails, plus clinical NLP pipeline work extracting medication data from notes for patient risk prediction.”

Ravindrareddy B

Screened

Junior Full-Stack Java Developer specializing in enterprise web applications

Ames, IA2y exp

“Full-stack engineer with hands-on experience building an internal telecom order-tracking/dashboard platform at T-Mobile across React, Spring Boot, and PostgreSQL. Stands out for owning features end-to-end, from scalable frontend architecture and TypeScript patterns to API design, query optimization, CI/CD, and post-launch monitoring in AWS CloudWatch.”

“Data engineer/backend engineer with healthcare domain experience at Centene, where they owned an end-to-end claims processing pipeline handling over 1 million monthly records. They combine Python/SQL pipeline work with API and event-driven service development, and cite a measurable 35% reduction in incident detection time through automated monitoring and validation.”

Jessy Kattupalli

Screened

Mid-level Full-Stack Java Developer specializing in enterprise web applications

West Haven, CT4y exp

“Backend engineer who built and scaled a transaction-processing microservice (150K+ records/day) in a microservices ecosystem, debugging peak-load latency/timeouts via CloudWatch/Grafana, Kafka lag analysis, and DB query tuning (indexes, Redis caching, batching). Also shipped an LLM-powered document assistant end-to-end with prompt/response validation plus retries/fallbacks for production reliability.”

“Backend engineer with TaskRabbit experience building and operating payment/booking services in Python/Django on AWS (ECS + Lambda) with Kafka/SQS eventing. Demonstrates strong production reliability and incident ownership in high-stakes payment flows (idempotency, strict timeouts, retries, monitoring/alerting) plus data/ETL work in AWS Glue and measurable SQL performance wins.”

“Backend/data engineer with hands-on production experience across GCP and AWS: built FastAPI microservices on Cloud Run and delivered AWS Lambda + ECS Fargate systems with Terraform/GitHub Actions. Strong in data engineering (Glue/Spark, S3/Redshift) and modernization (SAS to Python/SQL), with proven reliability and incident ownership—including cutting a 20+ minute reporting query to under 2 minutes.”