Vetted Azure Monitor Professionals

“Built and deployed a production LLM-powered RAG assistant for healthcare teams (care managers/support) to answer questions from clinical and policy documentation, emphasizing trustworthiness via improved retrieval, reranking, and strict grounding prompts to reduce hallucinations. Also has hands-on orchestration experience with Apache Airflow for end-to-end ETL/ML workflows and applies rigorous testing/metrics (hallucination rate, tool-call accuracy, latency, cost) to ensure reliable AI agent behavior.”

“Backend/AI engineer who has built production Spring Boot APIs on AWS (JWT auth, Redis/MySQL) and solved a real-world silent data integrity issue by implementing idempotency keys plus DB constraints/transactions. Also shipped an LLM-based document Q&A feature using a RAG pipeline with evaluation + human review, and designed multi-step agent workflows with verification, retries, and escalation guardrails.”

“Full-stack engineer with healthcare and finance experience who has owned end-to-end production systems across Azure and AWS. Built a real-time clinical dashboard at Centene (React + FastAPI + Azure Event Hubs) that cut data latency from ~12 minutes to under 1 minute and was associated with a 30% reduction in intervention delays. Also delivered MVPs in high-ambiguity environments at Accenture during monolith-to-microservices migration, improving uptime and maintainability with measurable results.”

Tejas Kolpek

Screened

Mid-level Solutions Architect/Engineer specializing in AI and data integrations

Mountain View, CA5y exp

“Solutions Engineer specializing in taking LLM copilots from demo to production, with a strong emphasis on enterprise security (RBAC/OAuth), grounded RAG behavior (cite-or-refuse), and operational readiness (eval loops, logging, runbooks). Experienced in real-time diagnosis of agentic/LLM workflow failures and in partnering with Sales/CS to run integration-first POCs that clear security and reliability concerns and accelerate rollout.”

Prasanth Sai

Screened

Mid-level Data Engineer specializing in cloud lakehouse/warehouse pipelines

4y exp

“Data engineer with HCA Healthcare experience building and operating end-to-end AWS-based pipelines for clinical and operational reporting (50–100 GB/day), serving curated data into Redshift/Snowflake for Power BI/Tableau. Emphasizes production reliability (Airflow SLAs/retries/alerting, logging/observability) and strong data quality controls (reconciliations, schema/null/duplicate checks), and has shipped versioned REST APIs to expose warehouse data to downstream systems.”

“Accenture data engineer who greenfielded a supply-chain lakehouse platform, building an end-to-end medallion/Delta pipeline ingesting ~1.4TB/day from 17+ ERP/WMS/TMS/shipment sources. Delivered Gold datasets to Redshift/Synapse/Databricks SQL powering Power BI/Tableau with a 99.5% SLA, while cutting runtime 30% and cloud costs 16% through Spark/Delta optimizations and robust data quality controls.”

Shashank R

Screened

Senior Data Engineer specializing in cloud data platforms and real-time analytics

Las Vegas, NV6y exp

“Data engineer (Credit One) who built and owned real-time financial transaction and credit risk/fraud data systems end-to-end on AWS + Snowflake. Delivered high-scale pipelines (150k events/hour; ~2TB/week), raised data accuracy to 99%, and cut Snowflake costs 42% while adding strong observability, schema-drift handling, and production-grade APIs/documentation.”

“Full-stack engineer with hands-on experience spanning React/TypeScript frontend architecture, .NET/Entity Framework backend services, and database optimization. Has owned end-to-end features like payment processing flows and also helped ship a 0→1 AI developer productivity capability, showing a mix of product sense, startup speed, and practical performance engineering.”