Vetted Amazon ECS Professionals

“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.”

“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.”

“AI engineer at Anote.ai who built and shipped a production multi-agent LangGraph/LangChain/Ray RAG platform for enterprise search and workflow automation, supporting 3 commercial products and 100+ developers. Drove measurable gains (30% accuracy improvement, lower latency) and improved reliability with Redis-based state checkpointing, message-queue synchronization, and Milvus retrieval optimizations, while partnering with PMs/clients to add transparency features like confidence scores and real-time logs.”

“Infrastructure/operations engineer with hands-on IBM Power/AIX administration (LPAR/DLPAR, HMC, RMC) and PowerHA cluster failover experience, plus modern DevOps tooling across CI/CD, Kubernetes/Helm, and IaC (Terraform/CloudFormation/Ansible). Emphasizes controlled change management, drift prevention via Git-as-source-of-truth, and observability practices using Prometheus/Grafana.”

Manjory saran

Screened

Senior Backend & Infrastructure Engineer specializing in cloud-native distributed systems

5y exp

“LLM infrastructure engineer who built a production-critical real-time personalization and memory retrieval system for a user-facing product, adding <100ms P99 latency while improving relevance ~20–25% and holding SLA through 3x traffic. Experienced designing tiered retrieval backends (Redis + vector store), deploying on Kubernetes with autoscaling/circuit breakers, and running rigorous observability, incident response, and agent evaluation (shadow traffic, A/B tests, regression/replay).”

“Backend-focused engineer who uses AI pragmatically as a force multiplier rather than a substitute for engineering judgment. They stand out for applying structured, agent-style workflows to code generation, debugging, and production log analysis while maintaining strong emphasis on correctness, performance, and reliability in backend and microservices environments.”

“Software engineer at Paradigm who is deeply hands-on with agentic development workflows and AI-assisted coding. He built an in-house OAuth layer to replace a third-party service and reduce projected integration costs, and also created an "ambient agent" that proactively responds to user behavior on the website. He stands out for combining full-stack architecture thinking with a disciplined, model-aware workflow for designing, implementing, and reviewing AI-generated code.”

“IBM-based cloud and AI engineer with hands-on experience owning Azure deployment workflows end-to-end, including IaC, DevOps automation, and cost/performance optimization. Also built an edge-first hospital event-detection workflow combining vision, LLM orchestration, and privacy-preserving local processing in a Nvidia/Dell hackathon that won first place.”