Vetted Amazon ECS Professionals

“Data/ML engineer in financial services (Northern Trust) who built a production RAG-based LLM system to connect structured transaction/portfolio data with unstructured market and internal documents for risk teams. Strong in end-to-end pipelines (AWS Glue/Airflow/PySpark), entity resolution, and taking models from prototype to reliable daily production with performance tuning (LoRA + TensorRT) and monitoring.”

“Founding AI engineer at an AI SaaS startup who built the full GTM knowledge and retrieval stack for non-technical teams, driving 60% less manual effort and 25% faster deployments. Also brings enterprise B2B SaaS integration experience from Wipro, including external API/documentation work for large-scale partner ecosystems.”

“Engineering leader with recent hands-on depth across TypeScript/React, Go, and Python who led a 15-person team through a zero-downtime migration from a legacy monolith to a Module Federation architecture. Has B2B SaaS experience in an insurance agent portal, combining security and performance work through RBAC, OAuth 2.0, and edge-based authentication.”

“Built a production AI-native internal onboarding feature that reduced manual product setup effort by combining barcode API data, product photos, structured LLM outputs, and a polished real-time camera UI. Demonstrates hands-on experience across the full stack of LLM systems: prompt/schema design, multimodal inputs, backend orchestration with SQS and vector retrieval, and production reliability through evals, telemetry, and drift monitoring.”

“Built across cloud infrastructure, AI-powered product workflows, and backend data reliability in environments including Northeastern, Knead, and Grafx. Particularly compelling for roles needing someone who can both ship AWS-based systems end-to-end and debug messy production issues involving caching, APIs, and data pipelines.”

Phanindra Satya Tharun Gunturi

Screened

Mid-level DevOps/SRE Engineer specializing in cloud CI/CD, IaC, and Kubernetes

Nashville, TN5y exp

“Infrastructure engineer with deep production IBM Power/AIX experience (AIX 7.2/7.3, HMC, dual VIOS, PowerHA) supporting ~25–30 LPARs and handling live DLPAR tuning, HA failovers, and Power7→Power9 migrations. Also builds modern cloud delivery platforms—Azure DevOps CI/CD deploying Dockerized microservices to Kubernetes with Terraform-managed AWS infrastructure, strong controls around secrets, drift, and safe rollouts.”

“LLM/agent production specialist with strong customer-facing and pre-sales chops: turns demo-grade prototypes into reliable, compliant deployments using RAG tuning, guardrails, evals in CI, and observability with staged rollouts/rollback. Known for engineering-first workshops (including live break-and-fix on retrieval misses, tool timeouts, and prompt injection) that win over skeptical senior developers and drive adoption.”

Job DelToro

Screened

Senior Full-Stack Engineer specializing in SaaS, cloud infrastructure, and video platforms

Guadalajara, México8y exp

“Full-stack engineer working at the intersection of product engineering and applied AI, with hands-on experience shipping real-time user features, MCP server integrations, and LLM-powered support systems. Stands out for combining TypeScript-heavy full-stack execution with production AI practices like retrieval architecture, confidence-based routing, observability, and evals, while driving measurable outcomes such as a 25% DAU lift and reduced support load.”

“Built and owned an enterprise AI document-processing deployment at an automotive tech startup, taking it from discovery to stabilization. Strong in production LLM/RAG systems and backend reliability, with measurable impact including 8,000+ documents processed monthly and turnaround time reduced from nearly 24 hours to about 3 hours.”

“Backend Python engineer who built core services for a telecom automation engine monitoring thousands of routers in real time and auto-generating support tickets. As the sole Intelygenz engineer on the project, they diagnosed a costly Terraform/GitLab CI/CD resource-leak issue in AWS and implemented a cleanup redesign that eliminated orphaned resources and reduced client cloud spend. Also shipped applied-AI ticket triage suggestions via API integration and built an end-to-end Gmail-to-ticket ingestion workflow.”

“Customer-facing software engineer who rapidly turns business requirements into Figma prototypes and PoC applications, using workflow prioritization and frequent client reviews to stay aligned. Has hands-on experience integrating with existing authentication/user APIs, building MongoDB-backed caching, and implementing robust fallback/retry mechanisms. Comfortable working on-site with customers and resolving production issues in AWS (e.g., DNS/EC2 traffic routing) in collaboration with DevOps.”

“ML/LLM engineer with production experience building a RAG-based LLM support assistant (FastAPI, Redis, Kafka) with multi-layer validation and human-in-the-loop feedback loops to improve accuracy over time. Has orchestration and MLOps depth using Airflow and Kubeflow on Kubernetes (autoscaling, alerting, monitoring) and delivered measurable ops impact (40% ticket efficiency improvement) by partnering closely with customer support teams.”