Vetted Amazon EKS Professionals

“Backend/platform engineer with experience across edtech, logistics, and AWS internal systems—owned a production course recommender end-to-end (model serving + APIs + caching/observability), delivering +30% CTR and -20% latency. Has scaled real-time delivery visibility/rerouting on Kubernetes/EKS to sub-200ms P95 during demand spikes and built billion-events/day telemetry pipelines on AWS (Kinesis Firehose, Lambda, S3, Redshift) with schema evolution, dedupe, and replay support.”

“Infrastructure/DevOps engineer with primary ownership in enterprise Linux and AWS/Azure production environments (including financial systems). Built secure, repeatable CI/CD pipelines deploying containerized workloads to EKS/ECS and implemented Terraform/CloudFormation IaC with drift detection and rollback practices; lacks direct IBM Power/AIX/PowerHA experience.”

“Backend/data engineer focused on compliance and statistical processing systems on AWS, building containerized FastAPI services plus event-driven async workflows (Step Functions/EventBridge) with strong reliability patterns (JWT auth, idempotency, structured logging). Has modernized SAS-based batch pipelines into modular Python/AWS services with parallel-run parity validation, and has demonstrated measurable SQL performance wins (40+ min to <10 min) and hands-on incident ownership using CloudWatch-driven detection and prevention.”

“Backend/data engineer with production experience building high-concurrency customer engagement platforms at KomBea on AWS (EKS + Lambda) using FastAPI/Django, PostgreSQL, Redis, and strong observability. Has modernized legacy batch systems into modular Python services with parallel-run parity validation and phased rollouts, and has delivered resilient AWS Glue ETL pipelines with schema evolution and data quality controls.”

“Amazon engineer who owned customer-facing Alexa features and built automation-heavy delivery practices (API/service-level testing in CI/CD) to ship quickly without sacrificing stability. Also built an internal self-service feature management/beta access platform (Angular + Spring Boot + event publishing) that replaced a multi-team ticket workflow with instant, auditable operations, and has deep microservices/Kafka experience with strong observability and reliability patterns.”

“Backend/platform engineer building HIPAA-compliant, real-time healthcare systems: owned a Python/Flask API layer for an AI-enabled patient engagement and risk scoring service, implemented PHI-safe logging and cross-service auditability, and delivered Kubernetes microservices via ArgoCD GitOps. Also has experience with Kafka streaming pipelines and hybrid cloud-to-on-prem migrations in regulated healthcare/fintech environments.”

“Built and shipped a production LLM-powered RAG assistant for enterprise internal document search (PDFs, knowledge bases, structured data), addressing real-world issues like noisy documents, hallucinations, and latency with grounded prompting, retrieval-confidence fallbacks, and performance optimizations. Also partnered with compliance and business teams at JPMc to deliver a solution aligned with regulatory constraints, supported by monitoring, feedback loops, and systematic evaluation.”

“Engineer with Securonix experience deploying and operating production microservices and real-time data-processing systems at high throughput. Led AWS infrastructure, CI/CD, monitoring, and customer-driven customization for a threat-report classification solution, including rule adjustments and model retraining based on live client feedback.”

“AI/LLM engineer with Fidelity Investments experience who built and shipped a production GraphRAG system that augmented prompts with codebase context, improving business analyst efficiency by 15% and saving ~$3.5M annually. Strong in AWS EKS/Kubernetes/Helm and enterprise IAM/OIDC patterns (including cross-account S3 access), with experience mentoring interns and collaborating with non-technical leaders to extend AI pipelines (e.g., adding SQL functionality during MVP).”

“Software engineer who owned an end-to-end self-service reporting workflow (secure APIs, async/batched processing, and React UI), improving report generation performance by ~30–40% and reducing manual support effort. Also built a RAG/embeddings prototype over internal docs and service logs with grounding-focused guardrails, and has a strong reliability/observability mindset (retries, DLQs, CI/CD validation, dashboards/tracing) for distributed workflows.”