Vetted Azure App Service Professionals

“Frontend engineer who has led enterprise-scale UI delivery end-to-end on a microservices platform, designing modular Angular SPAs (v12-17) tightly aligned to Spring Boot REST APIs. Emphasizes quality and release velocity through layered testing (Karma/Jasmine), CI/CD automation (Jenkins/Azure DevOps), performance tuning with RxJS/lazy loading, and incremental rollouts with close product/design/QA collaboration.”

“Backend engineer with Walmart experience owning Python data-processing/integration services alongside ASP.NET Core. Has deployed containerized services to Kubernetes via OpenShift with Jenkins CI/CD and GitOps-style config management, and has led phased migrations modernizing VB6/classic ASP apps to ASP.NET Core on OpenShift/Azure. Also implemented Kafka-based real-time pipelines with a focus on reliability, idempotency, and observability.”

“Azure cloud platform engineer with strong enterprise Linux operations background who designs multi-region HA/DR on Azure (and AWS) using Azure Site Recovery, Traffic Manager, AKS autoscaling, and geo-replicated Azure SQL. Built secure Azure DevOps CI/CD pipelines for .NET/Python microservices to AKS/VMs and provisions full environments via Terraform modules with remote state, drift checks, and staged rollouts; has not directly owned IBM Power/AIX at scale.”

“Currently at Huntington Bank, built a production-grade RAG system that helps business/operations teams get grounded answers from large volumes of internal enterprise documents. Owns ingestion and FastAPI backend, tuned hybrid BM25+vector retrieval and chunking for relevance, and evaluates reliability with metrics and observability (LangSmith, CloudWatch, Prometheus/Grafana) while partnering closely with non-technical stakeholders.”

“Built Nexthire-AI, shipping an end-to-end LLM-powered resume–job description matching product (React + Node.js) using embeddings and retrieval to generate match scores and skill-gap recommendations. Improved post-launch engagement by making feedback cleaner and more actionable, and added production guardrails (validation, timeouts, fallbacks) to handle messy resume formats and AI API instability.”

“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.”

“Backend engineer who built an e-commerce order processing service in Python/Flask with PostgreSQL, focusing on correctness and reliability (idempotency, Redis locks, async payment processing with circuit breakers). Also integrated an ML recommendation system as a separate FastAPI inference service with caching and async embedding updates, reporting ~25% CTR lift, and has experience with multi-tenant isolation using PostgreSQL row-level security.”

“Full-stack Java developer with IBM and Epic Systems experience modernizing legacy enterprise apps into microservices and delivering customer-facing healthcare claims workflows at very high scale (2M+ transactions/day). Strong blend of product engineering (APIs + React/TypeScript UI) and production operations on AWS, including performance incident remediation via query optimization, indexing, and autoscaling.”

“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.”

“LLM/GenAI engineer with US Bank experience building a production financial-document intelligence platform using LangChain/LangGraph, GPT-4, and Amazon OpenSearch. Delivered a RAG-based assistant for compliance/audit teams with grounded, cited answers, focusing on reducing hallucinations and latency, and deployed securely on AWS (SageMaker/EKS) with CI/CD and evaluation tooling (LangSmith, RAGAS).”

“Software engineer at Procter & Gamble focused on warehouse/operations systems, building near-real-time order/inventory visibility using Java/Spring Boot, React, Kafka, PostgreSQL, and Redis with measurable latency and load-time gains. Also shipped internal LLM/RAG knowledge assistants grounded in company runbooks and workflows, implementing guardrails and an evaluation loop that drove concrete retrieval improvements (document chunking) and regression prevention.”

“Full-stack Java engineer (4+ years) who led end-to-end modernization of high-latency order management systems into cloud-native reactive microservices (Spring WebFlux) and built real-time React/Redux dashboards, reporting 99.98% uptime and 22% infra cost savings. Also headed a production RAG-based Order Support Bot at Dell Technologies with embeddings + MongoDB semantic search, automated validation and human fallback, plus CI/CD-driven LLM eval loops to reduce hallucinations.”

“Backend/DevOps engineer pivoting into robotics/space, building hands-on ROS2 (Humble) skills via Gazebo simulations and experimenting with Nav2 and slam_toolbox. Brings strong distributed-systems and real-time debugging practices (profiling, instrumentation, QoS/retry patterns) and is actively learning perception and control fundamentals to transition into autonomous robotics.”

“Unity/gameplay engineer (Playtika) who built a state-machine/ECS-driven slot/bonus engine in a client-server setup, focusing on consistent outcomes under latency and highly engaging reward sequences. Also implemented server-authoritative real-time challenges/contests via an event-driven messaging system (SignalR-like) across iOS/Android/WebGL/UWP, and validates impact through retention/session/engagement analytics.”

“Full-stack engineer with experience at Vanguard, PNC, and Humana building customer-facing investment/banking flows and internal ops tools using Angular/React/TypeScript with Spring Boot microservices. Strong in shipping time-sensitive changes safely via automated testing/CI (JUnit/Mockito, Jenkins, SonarQube) and in operating event-driven microservices with Kafka (idempotency, retries, correlation IDs). Improved internal tool adoption by responding to ops/support feedback with query optimization and clearer search results.”

“Backend engineer with PayPal experience owning a high-throughput, low-latency fraud detection pipeline processing billions of transactions/day, integrating LLM-based models into real-time Kafka streams and payment decisioning APIs. Strong Kubernetes + GitOps practitioner (declarative, auditable deployments; autoscaling/probe tuning) with migration experience modernizing legacy systems onto AKS/OpenShift.”

“Backend engineer who built a containerized Flask service powering an engineering metrics dashboard by syncing GitHub and Jira data into PostgreSQL, with strong emphasis on schema design, query performance, caching, and background processing. Has hands-on experience with SaaS multi-tenancy (tenant scoping + Postgres RLS) and integrating AI/ML inference via separate model-serving services (FastAPI + TensorFlow Serving) and external APIs (OpenAI/Hugging Face/PyTorch).”

“Software engineer with Citi Bank experience building real-time fraud validation/scoring for loan processing, spanning Spring Boot microservices and a FastAPI Python service secured with OAuth2/JWT. Delivered React/TypeScript operations dashboards and deployed containerized services via Docker/Kubernetes with Jenkins CI/CD, while also tuning databases (Oracle/Postgres) and handling high-volume latency/scaling issues using ELK, caching, and autoscaling on AWS.”

“Backend-leaning product engineer with DevSecOps depth who has shipped real-time, Kafka-driven data pipelines and AI-enabled customer-facing features to production on AWS. Built a Spring Boot API layer serving real-time predictions at 100K+ requests/day, improving latency by 35% and user task completion by ~25%, and delivered a React/TypeScript dashboard plus a Postgres audit/history model optimized for search and large event volumes.”

“Backend engineer who has built high-throughput analytics and fraud-detection systems, combining Python/Flask + Celery/RabbitMQ with strong PostgreSQL performance tuning (indexing, partitioning, EXPLAIN ANALYZE). Has production experience integrating ML inference (scikit-learn/TensorFlow → TensorFlow Lite) into Spring Boot microservices with caching and model versioning, plus designing secure multi-tenant architectures using JWT-based tenant routing and PostgreSQL RBAC/RLS.”

“Backend engineer with Citi Bank experience building and operating a Python/Flask Personal Finance Manager platform at 1M+ transactions/month. Strong in secure API design, database performance tuning (PostgreSQL/Azure SQL), and production reliability (92%+ test coverage, load testing, monitoring). Also integrated an NLP expense-tagging microservice with caching, background workers, autoscaling, and multi-tenant isolation via RLS and tenant-aware JWT.”

“Backend/data engineer with hands-on production experience building reliable Python FastAPI services on Kubernetes and delivering AWS EKS + Terraform CI/CD with strong secrets isolation and rollback practices. Also built AWS Glue ETL pipelines into S3/Redshift with schema-evolution handling and data-quality controls, modernized legacy analytics into modular Python services with parallel-run parity validation, and has demonstrated SQL tuning impact (minutes to seconds) plus ownership of batch pipeline incidents end-to-end.”

“GenAI/RAG engineer who has deployed a production policy/regulatory search assistant for a financial client using LangChain + Vertex AI, FastAPI, Docker/Kubernetes, and Airflow-orchestrated data pipelines. Demonstrated measurable impact with 50–60% latency reduction and 70% fewer pipeline failures, plus KPI-driven grounding evaluation (90%+ target) and strong cross-functional collaboration with compliance/business teams.”