Vetted Amazon CloudWatch Professionals

Mazhar Haq

Screened ReferencesStrong rec.

Senior AWS Cloud Architect and Technical Leader specializing in security, migrations, and cost governance

Santa Monica, CA26y exp

“Infrastructure/platform engineer with strong AWS and hybrid on-prem networking depth, spanning Kubernetes platform engineering (IaC, autoscaling, GitOps, observability) and large-scale VMware operations. Managed thousands of VMs across 56 US military bases/airports and has resolved real production hybrid incidents involving BGP/Direct Connect route advertisement and prefix-limit constraints.”

Manaswini Gogineni

Screened ReferencesStrong rec.

Mid-Level Software Engineer specializing in cloud infrastructure and full-stack web development

San Francisco, CA2y exp

“Backend engineer at Electric Hydrogen who built a serverless device-log ingestion and processing platform in Python/Flask, scaling throughput (4x peak ingestion) while keeping sub-300ms API latency. Strong in Postgres/SQLAlchemy performance (partitioning, materialized views) and production ML integration (ONNX model served via FastAPI microservice with async batch inference, Redis feature caching, and drift monitoring via S3/Lambda). Experienced designing secure multi-tenant systems with schema-per-tenant isolation and KMS-backed encryption.”

“Backend/AI engineer who has built a rule-service platform on AWS and evolved it into an agentic RAG system using LangChain, ReAct, tool calling, and LLM-as-judge review. Notable for combining heavy AI-assisted development with production safeguards like manual CR, CloudWatch monitoring, fallback strategies, benchmark testing, and user-feedback-driven model improvement.”

“Senior engineering leader at AWS currently managing two services in the MSK organization, including Replicator for disaster recovery/data distribution and Glue Schema Registry. He combines hands-on distributed systems depth with large-scale people leadership, having managed teams up to 32 engineers and coordinated platform onboarding work across roughly 340 AWS services. Earlier experience in payroll and compliance platforms adds strong enterprise domain breadth beyond cloud infrastructure.”

Nikhil Reddy

Screened

Mid-level AI/ML Engineer specializing in GPU inference and LLM platforms

San Francisco, CA5y exp

“Built and deployed an LLM-powered platform that turns models into scalable REST/gRPC APIs, focusing on keeping GPU-backed inference fast and stable during traffic spikes. Experienced with AWS orchestration (EKS/ECS/Step Functions), safe model rollouts, and production-grade monitoring/testing for reliable AI agents and workflows.”

Pranav Hariharane

Screened

Mid-Level Backend Engineer specializing in REST APIs and AWS

SF Bay Area, CA3y exp

“Backend engineer who built a new REST eligibility service at Barclays that unified siloed account logic (card/loan/deposit) and integrated with web/mobile, ultimately serving millions of users daily. Also built an end-to-end LLM-based pharmaceutical care-plan generation tool in a rapid Columbia startup competition, emphasizing configurable design, strict validation, persistence, and robust error handling.”

Kunj Amrutbhai Patel

Screened

Mid-level Software Engineer specializing in distributed backend systems on AWS

Seattle, WA4y exp

“Built production systems in the AWS ecosystem, including an internal AI assistant for diagnosing account transfer and permissions issues and an end-to-end account transfer workflow used by enterprise customers. Stands out for combining LLM/RAG design with strong distributed systems reliability practices, emphasizing guardrails, fallbacks, and operational trust in high-stakes workflows.”

“Built and shipped an AI-powered resume analysis and job-matching product end to end across React, TypeScript, FastAPI, OpenAI, LangChain, and FAISS. Strong in practical LLM systems design, including RAG, structured outputs, evals, monitoring, and human-in-the-loop decision support, with a reported 35% improvement in recruiter-validated matching accuracy.”

“Full-stack engineer with Uber experience building finance/billing reconciliation systems: shipped and owned an internal operations dashboard (Next.js App Router/TypeScript) that cut investigation time from hours to minutes and improved load time from ~6–7s to <2s. Deep in Postgres modeling and performance (sub-200ms optimized queries) plus durable event-driven workflow orchestration with idempotency, retries/backoff, DLQs, and reconciliation jobs; also has seed-to-Series C startup experience emphasizing end-to-end ownership.”

Aniket Singhal

Screened

Senior Software Engineer specializing in AWS-based distributed systems and FinTech platforms

Seattle, WA8y exp

“Backend engineer with Amazon experience building large-scale, automated financial/accounting and pricing systems on AWS. Designed a fault-tolerant Step Functions + DynamoDB workflow platform handling 100K+ messages/sec to compute fair values and generate journal entries in under 3 seconds, and led safe API refactors using shadow mismatch testing. Also uncovered a major legacy pricing bug (tax vs non-tax swap) that cut mismatch rates from 5–10% to ~0.5% and materially improved price acceptance/business outcomes.”