Vetted AWS CloudFormation Professionals

“DevSecOps/AWS infrastructure engineer at Madison Logic who owns a 15-account AWS footprint and treats nearly all AWS resources as code (Terraform/CloudFormation). Led a CI/CD platform migration (Bitbucket → GitLab + GitHub Actions) supporting WordPress and containerized microservices, improving release frequency to weekly/daily, and has hands-on production incident response experience on ECS Fargate using Datadog with fast rollback via immutable ECR tags and task definition revisions.”

“Application-layer full-stack engineer who has shipped enterprise-facing integrations and developer tooling, including an end-to-end Slack integration for automated ticket creation and a real-time feature-flag dashboard (React/TS + GraphQL/Apollo + NestJS) with audit trails. Has hands-on AWS container operations experience (ECS Fargate/ALB/RDS) and has improved product performance (35% faster dashboards) while building auth and RBAC for 500+ users.”

“Accenture engineer with hands-on experience taking an NLP sentiment analysis system from prototype to production, emphasizing robustness to noisy data, scalability, and observability (dashboards for latency/error/throughput). Also supports customer-facing teams with demos and PoCs, translating client requirements into secure, scalable architectures and troubleshooting LLM/agent workflows via logs and step-level traces.”

“End-to-end engineer focused on AI-native enterprise systems, including a production generative knowledge platform using RAG + semantic search over internal documentation (React, Python/Flask, GPU-hosted NLP models, Pinecone) with strong CI/CD and observability. Reports concrete outcomes including 40% faster knowledge access and ~75% employee adoption, and has led incremental cloud-native modernization using feature flags, parallel runs, canary releases, and regression testing.”

“AI Engineer at Humanitarian AI who has built and productionized both a LangGraph-based multi-agent workflow system and a RAG pipeline (OpenAI embeddings + vector DB) with rigorous evaluation/guardrails. Reports strong measurable impact (60% faster workflow delivery, 40% fewer incidents, 70% reduced research time) and has prior enterprise modernization experience at Infosys migrating ETL to microservices with zero production incidents.”

“Built a production "Mini RAG Assistant" for internal document Q&A, focusing on grounded answers (anti-hallucination), retrieval quality, and latency/cost optimization. Uses LangChain/LangGraph for orchestration and applies a metrics-driven evaluation loop (including reranking and semantic chunking improvements) while collaborating closely with product stakeholders.”

“Engineer with experience in regulated healthcare and financial systems, including a United Health healthcare service migration to AWS. Built documentation-as-code for CI/CD (Jenkins/Docker/Kubernetes/Terraform + GitHub Actions) that accelerated release cycles from 3 weeks to 4 days and tied security configuration (Spring Security/OAuth2/JWT) directly to HIPAA/GDPR compliance. Strong in observability-led incident response (ELK/Prometheus/Grafana) and performance tuning (PostgreSQL, async processing), citing MTTR reduction from 3 hours to 50 minutes and support for 250K+ concurrent users.”

“Enterprise workflow/product engineer (DXC) who owned a customer-facing workflow application for 500+ users and improved performance ~30% through API/SQL optimization, caching, and CI/CD-backed iteration. Experienced designing React/TypeScript + Java/Spring Boot systems and operating microservices with RabbitMQ/Kafka-style messaging, emphasizing reliability via DLQs, backpressure, and strong observability. Also built an internal automation dashboard adopted by support/ops teams to cut manual work and reduce SLA misses.”

“Full-stack engineer focused on data-heavy platforms, building Spring Boot microservices and Angular/React dashboards end-to-end. Has hands-on experience improving large-scale API and UI performance (including cutting 8–10s response times) and ensuring cross-service consistency using Kafka, idempotent consumers, and strong validation/transaction patterns on AWS with CI/CD and observability (Prometheus/ELK).”

“Full-stack engineer who built a cloud-native customer servicing platform at Synchrony using React 18/Next.js (SSR) and Spring Boot microservices on AWS. Experienced with high-volume, event-driven systems (Lambda/SNS/SQS) and strong distributed-systems rigor around data integrity (idempotency, DynamoDB conditional writes) plus production-grade security/observability (JWT/OAuth2, WAF, Actuator, Splunk).”

“Cloud/platform engineer with hands-on delivery across Azure and AWS, including standing up a CIS-compliant Azure environment and integrating Azure OpenAI Foundry to automate finance invoicing. Has scaled platform capabilities across large org footprints (dynamic CI/CD pipelines for ~94 teams across 200+ repos) and replaced a $1M/year vulnerability patching vendor by building an internal AWS-based patching and monitoring solution for ~1000 servers.”

“Backend/data engineer with hands-on production experience across Python/Flask microservices and AWS serverless/data platforms (Lambda, DynamoDB, S3, Glue/PySpark). Demonstrated strong reliability and operations mindset (JWT/RBAC, retries/timeouts/circuit breakers, CloudWatch/SNS alerting) and measurable performance wins (SQL report runtime cut from 10 minutes to 30 seconds). Seeking ~$150k base and cannot travel for onsite meetings for the next 5–6 months due to family medical constraints.”

“At Unar Labs, built and operationalized LLM capabilities inside a cloud-native SaaS product, emphasizing production reliability (fallbacks, observability, cost/latency/quality monitoring) and iterative improvement from user feedback. Also acts as a customer-facing technical lead—running developer demos/workshops and supporting sales through discovery, pilots/POCs, and technical walkthroughs to drive production adoption.”

“Backend/data engineer with aerospace telemetry and reporting experience across RTX and other orgs, spanning Python/FastAPI microservices, AWS serverless/containers, and AWS Glue-to-Redshift analytics pipelines. Has led legacy modernization with parallel-run parity validation and incremental rollout, and demonstrates strong operational ownership (monitoring, incident response, and cost optimization).”

“IBM Power/AIX engineer who has owned a 150+ LPAR AIX 7.x estate with VIOS/HMC/vHMC and PowerHA in production, including real outage and failover recoveries. Also brings modern DevOps/IaC experience—built Jenkins pipelines deploying to AKS and implemented Terraform on AWS with remote state, locking, and drift management.”

“Full-stack intern at Rebel who owned backend work on a cross-platform music platform using Python/Django with MongoDB, implementing user-focused REST APIs end-to-end. Also built CI/CD pipelines (Jenkins/GitHub Actions) to containerize and deploy to AWS, and has experience integrating Kafka-based real-time event processing with reliability and observability practices.”

“Built a production lead-generation system using AI agents that researches the internet for relevant leads and integrates RAG-based contact enrichment/shortlisting aligned to existing CRM data, enabling sales reps to focus more on selling. Also has hands-on AWS data orchestration experience (Glue, Step Functions) moving raw data into Redshift and evaluates agent performance with human-in-the-loop plus BLEU/perplexity metrics.”

“Backend engineer who evolved Coca-Cola bottlers' Trade Promotion Optimization platform at Coke One North America, building domain-focused microservices in Node.js and Python (Flask/FastAPI) with PostgreSQL. Experienced in multi-tenant security (OAuth2/JWT, RBAC, row-level scoping by bottler/region), API contract/versioning discipline, and Azure DevOps-driven incremental rollouts with strong observability.”

“Full-stack/ML-leaning engineer who has shipped production-grade real-time analytics and an internal AI support assistant using RAG over enterprise documentation. Demonstrates strong systems thinking across scalability, reliability, observability, and LLM safety/evaluation (thresholded retrieval, RBAC, response validation, regression-gated evals), with concrete iteration based on performance metrics and user feedback.”

“Cloud/infrastructure engineer with strong production operations background across AWS, Azure, and Kubernetes, supporting 30+ enterprise workloads for ~40,000 users. Demonstrated incident leadership (hybrid AKS-to-AWS routing outage) with a reported 60% MTTR reduction, plus hands-on CI/CD (Jenkins) and Terraform-based IaC for AWS (VPC/EC2/EKS). Lacks direct IBM Power/AIX/PowerHA experience but emphasizes transferable ops and troubleshooting skills.”

“Full-stack engineer with strong DevOps/AWS experience who ships end-to-end React/TypeScript + Node/Python systems and operates them in production. Built an LLM-assisted recommendations workflow for a SaaS product with robust reliability controls (schema-validated JSON outputs, fallbacks, caching, monitoring) and measured impact via adoption, time saved, and override rates; also experienced delivering MVPs fast in early-stage startup ambiguity.”

“Backend engineer experienced in evolving high-scale legacy on-prem systems into cloud-native, event-driven microservices on AWS/Kubernetes (noted peak traffic ~1.5M QPS). Strong focus on reliability engineering and operational excellence—SLO-driven observability, GitOps/canary rollouts, chaos testing, and preventing cascading failures (e.g., retry-storm mitigation).”