Vetted Amazon ECS Professionals

“Platform/infra engineer with strong ownership of Kubernetes on VMware and day-to-day hybrid on-prem-to-AWS operations. Has hands-on experience automating infrastructure delivery with Terraform/Ansible/CI-CD, and has resolved real production issues spanning CSI storage reattachment during upgrades, vSphere storage-latency performance degradation, and hybrid connectivity/routing failures with improved validation, monitoring, and failover.”

“Backend/AI systems engineer who has shipped production LLM agents focused on prompt engineering, code generation, and incident-response automation. Stands out for combining strong agent orchestration and reliability engineering with measurable business impact, including 60-70% cost reductions, 45% lower monthly LLM spend, and a 5x increase in developer iteration speed.”

Tara Munjuluri

Screened

Junior Software Engineer specializing in full-stack and AI systems

Ames, IA3y exp

“Backend-focused engineer with end-to-end ownership experience on internal platforms at John Deere, including a workforce and skills system that cut manual review time by 40%. Brings a strong reliability and compliance mindset across Java/Python microservices, AWS infrastructure, and production operations, and has also built an LLM-powered RAG system over 1M+ records with emphasis on grounded outputs and observability.”

“Backend engineer with experience at JPMorgan Chase and Walgreens, owning transaction-processing and prescription data flow systems in regulated environments. Brings strong hands-on depth in Spring Boot microservices, Kafka, Redis, Kubernetes, observability, and production incident resolution, plus practical experience integrating OpenAI-powered workflows with validation and fallback safeguards.”

“Backend/platform engineer with deep payments experience who built and operated a real-time transaction routing service end-to-end on AWS (Spring Boot, PostgreSQL/RDS, Redis, Kubernetes), delivering ~40% latency reduction and 99.99% uptime via strong resiliency and observability practices. Also productionized an internal LLM-powered RAG knowledge assistant with guardrails and a user-feedback-driven evaluation loop, and has led incremental monolith-to-microservices modernization using Strangler Fig and shadow traffic.”

Ruturaj Ghatage

Screened

Junior Software Engineer specializing in full-stack, cloud infrastructure, and applied AI

Herndon, Virginia2y exp

“Master’s student at UC San Diego who built an LLM-powered healthcare chatbot for patient history-taking and sepsis-related output, using a Node.js backend integrated with FastAPI for RAG/LLM interactions and a Flutter client. Also has healthcare AI startup experience deploying on AWS (ECS/Terraform/Docker) and implementing Kubernetes autoscaling to improve efficiency and reduce costs, with strong iterative evaluation in collaboration with a physician.”

“ML/AI engineer with hands-on ownership of production document intelligence and GenAI systems, spanning model experimentation, AWS deployment, monitoring, and iterative optimization. Stands out for turning document-heavy workflows into reliable, near real-time products with measurable gains in accuracy, latency, and manual-effort reduction, while also shipping citation-grounded RAG features that drove user trust and adoption.”

Michael Matonte

Screened

Senior Backend Engineer specializing in distributed systems and AI-enabled platforms

Jersey City, NJ7y exp

“Backend engineer with end-to-end ownership experience in high-stakes environments spanning Citibank and industrial operations. They built an internal banking platform that automated complex entitlement workflows across thousands of business units with an 80% reduction in redundant processing, and they are now applying AI through OpenAI-powered agent workflows with RAG, vector databases, and security controls.”

Harsh Sanas

Screened

Junior Full-Stack Engineer specializing in AI systems and cloud applications

San Francisco, CA2y exp

“Full-stack engineer with a strong applied AI bent who has built both a real-time EV charging platform and a production text-to-SQL system. Particularly compelling for teams needing someone who can bridge frontend, backend, infrastructure, and LLM evaluation/safety work, with experience shipping under early-stage ambiguity and integrating software with real-world hardware.”

“Backend/data engineer from ASML who modernized a legacy SAS-based statistical processing system into a cloud-native AWS platform (Lambda/FastAPI, Step Functions/EventBridge, Glue, S3/RDS) with strong reliability and data-quality practices. Demonstrated measurable performance wins (RDS query reduced from 90+ seconds to <5 seconds) and hands-on incident ownership for production ETL pipelines.”

“Backend/data engineer with hands-on production experience across Python/FastAPI services and AWS (Lambda, API Gateway, SQS, ECS) delivered via Terraform and GitHub Actions. Built Glue-to-Redshift ETL pipelines with Step Functions retry/catch patterns, schema evolution safeguards, and data quality checks; also modernized a legacy SAS monthly reporting system into Python microservices with rigorous side-by-side parity validation. Demonstrated strong SQL tuning skills with a reported improvement from 5 minutes to 15 seconds.”

“AI-native software engineer who uses agentic development as a core workflow, including a three-agent setup for planning, validation, and implementation. In their most recent role, they acted as the lead orchestrator for AI agents, with a strong emphasis on production safety, architectural control, and rigorous validation.”

Nilesh Dixit

Screened

Executive AI engineering leader specializing in agentic AI and enterprise platforms

San Francisco, CA24y exp

“Bay Area engineering leader and startup co-founder with a rare mix of deep hands-on architecture experience, large-scale people leadership, and cross-functional product ownership. He helped launch GE Digital's industrial IoT efforts, holds multiple patents in the space, has scaled teams to 60-70 people, and has led both enterprise platform modernization and AI startup product development.”

“Healthcare-focused full-stack/platform engineer with recent hands-on experience in Go, React, Python, Kubernetes, and AWS. They have worked in high-reliability, compliance-heavy environments, driving infrastructure modernization, internal operational tooling, and observability improvements that reduced troubleshooting friction for clinician platform and support teams.”

“SRE-focused engineer with experience at Sony Interactive Entertainment productionizing high-throughput LLM/agentic systems on Kubernetes, including GPU-aware autoscaling and warm-pool strategies to manage latency and cost under traffic spikes. Demonstrates strong incident response using Prometheus/Grafana + Jaeger tracing (e.g., resolving recursive agent loops and restoring 99.9% availability within minutes) and partners closely with sales/customer teams through PoV demos and developer workshops.”