Vetted Idempotency Professionals

“Solo-built and launched an AI logo generator SaaS in ~2 months using React/Next.js/TypeScript with managed auth and payments, deploying via Vercel/GitHub CI/CD. Also has hands-on AWS production experience running containerized services with Terraform-managed multi-environment infrastructure and strong reliability patterns for integrations/pipelines.”

“Full-stack engineer who shipped a group scheduling SaaS feature with live availability updates using Next.js App Router + TypeScript, owning production reliability after launch (auth debugging, monitoring, polling/backoff tuning). Has hands-on experience with Postgres schema/index design and query optimization (EXPLAIN ANALYZE) and building durable orchestrated backend workflows with retries and idempotency.”

“Built an NYU software engineering capstone called “Smart Cash AI,” a multi-agent LLM-powered web app that curates offline-ready podcasts/articles/videos/news based on user preferences and commute schedules. Architected agent orchestration (discovery/downloader/summarizer), real-time progress via WebSockets, and an ETL normalization layer across RSS/YouTube and other sources with GUID-based deduplication, retries, and failure isolation to keep the system predictable.”

Sanket Dumbare

Screened

Mid-Level Software Engineer specializing in cloud-native microservices and FinTech platforms

USA3y exp

“Backend/platform engineer who led an end-to-end Python (FastAPI) transaction analytics microservice for real-time financial monitoring, including SQS ingestion, scoring/aggregation, and low-latency APIs. Strong AWS + Kubernetes/GitOps background (EKS, ArgoCD, Jenkins, ECS/ECR, CloudWatch) with hands-on experience scaling event-driven systems and executing phased on-prem to AWS migrations.”

Deeresh Gajjala

Screened

Senior Software Engineer specializing in Java/Spring Boot microservices and AWS payments systems

Dallas, TX6y exp

“Senior software engineer with Amazon experience who owned end-to-end improvements to a real-time payment authorization service, rebuilding it as a reactive Spring WebFlux microservice with saga orchestration and Kafka event streaming, deployed on AWS EKS with strong observability. Also built React+TypeScript and Node/Express full-stack workflow apps (onboarding, campaign management, admin review) and has experience shipping quickly in ambiguous startup environments while maintaining reliability and data correctness.”

Sreelekha Vuppala

Screened

Mid-level Data Scientist specializing in Generative AI, MLOps, and cloud data platforms

USA4y exp

“GenAI/ML engineer (CitiusTech) who has deployed production RAG systems for compliance/operations document Q&A, using Pinecone + FastAPI microservices on Kubernetes with strong monitoring and guardrails. Also built a GenAI-powered incident triage/routing solution in collaboration with non-technical stakeholders, achieving 35% faster response times and 40% fewer misclassified tickets, and has hands-on orchestration experience with Airflow and AutoSys.”

“Data engineer who has owned end-to-end production pipelines processing a few million records/day, using Python/Airflow/SQL/PySpark with Snowflake serving to BI (Power BI). Built resilient external web data collection systems (anti-bot, schema-change detection, backfills) and shipped versioned REST APIs for internal consumers, improving pipeline success rates to 99% through monitoring, retries, and idempotent design.”

Jaskirat Singh

Screened

Mid-level Software Engineer specializing in cloud infrastructure and data platforms

Eden Prairie, MN5y exp

“Infrastructure/data platform engineer with hands-on GCP production experience, especially Bigtable, who led a migration from Azure Cosmos DB Cassandra API to Bigtable that removed throttling and cut costs by 50%+. Stands out for combining distributed data architecture, zero-downtime Kafka migration strategy, and Terraform/Python automation for deterministic multi-region GKE operations.”

Aravind Mohan

Screened

Junior Software Engineer specializing in AI agents and backend systems

Seattle, WA5y exp

“Backend/AI workflow engineer who built a production event-personalization service (FastAPI + AWS Lambda) and solved real-world reliability/latency issues with deterministic routing, caching, and query/index optimization. Also built an end-to-end Gmail-based job application tracking agent using a lightweight RAG pipeline with Gemini, strong guardrails (Pydantic schemas, confidence thresholds), and offline regression tests to prevent drift and hallucination-driven data corruption.”

“Built both traditional internal tooling and LLM-powered systems during an internship, including a React/Python/AWS calculator onboarding platform and a production-style ROS2 RAG assistant over 10K+ documents. Stands out for combining full-stack delivery, stakeholder coordination, and practical AI reliability work like retrieval tuning, source-grounded answers, and low-confidence fallbacks.”

“Backend/full-stack engineer with Blue Cross Blue Shield experience building a reactive, event-driven claims processing microservice platform on AWS (ECS, SNS/SQS) with Terraform-based IaC and strong observability (Dynatrace/CloudWatch). Demonstrated measurable production impact (32% less downtime, 24% higher processing efficiency) and deep database performance/migration expertise across MongoDB and Postgres.”

Ajay Desai

Screened

Mid-level Full-Stack Software Engineer specializing in FinTech and backend platforms

USA4y exp

“Built an AI-native legal research platform that automated analysis across 100,000+ dense legal documents, combining LLM workflows, async backend architecture, and conversational retrieval in production. Also brings cross-domain experience in investment-analysis agents and healthcare claims/billing systems, with a strong emphasis on reliability, deterministic orchestration, and safe handling of messy operational data.”

“Full-stack engineer with deep experience building enterprise compliance and certification systems at Paycom, including complex approval workflows, live migrations, and large-scale assignment processing. Particularly strong at turning ambiguous business rules into reliable backend workflow logic and at designing trustworthy GraphQL/AI-assisted user experiences backed by real-time system data.”

Sanket Mungikar

Screened

Mid-level Software Engineer specializing in distributed backend and AI analytics platforms

California, USA4y exp

“Full-stack engineer at BigCommerce who combines customer-facing deployment ownership with hands-on AI/LLM systems work. Built and launched merchant analytics and predictive inventory workflows using React, TypeScript, FastAPI, Kafka, AWS, and RAG-style architectures, and has real production experience debugging non-deterministic AI issues caused by data pipeline freshness and event-ordering problems.”

“Full-stack product engineer who has built both operational systems and enterprise AI copilots in production. They owned an AI-powered inventory platform end-to-end, driving a 45% drop in stock issues, and also shipped a Microsoft Teams-based HR/IT copilot using RAG and workflow automation that reduced repetitive support queries by roughly 30%.”

“Built an internal AI-powered document search and Q&A platform at BNY that let employees query company documents in natural language and get grounded answers in seconds. Brings practical full-stack and LLM systems experience across React/TypeScript, FastAPI, Pinecone, OpenAI, and Claude, with clear emphasis on retrieval quality, hallucination reduction, and production monitoring.”

PrabhjyotKaur Bamrah

Screened

Mid-level Full-Stack Software Engineer specializing in enterprise apps and AI integration

Redwood City, CA4y exp

“Engineer with experience scaling enterprise AI products in production, including a C3 AI deployment expanded from 2 to 4 sites across the US and Canada. Also built a GPT-4o-powered RAG assistant for plant operators, combining structured and unstructured data with human-in-the-loop safeguards and iterative evals to improve answer quality.”

“Candidate indicated they live in New York but did not provide substantive details about their experience; they declined to discuss at least one topic as restricted and did not answer role-related questions with concrete examples.”

“Backend/platform engineer who owned a real-time customer analytics microservice stack in Python/FastAPI with Kafka streaming into PostgreSQL, including schema enforcement (Avro) and high-throughput optimizations. Strong Kubernetes + GitOps practitioner (EKS/GKE, Helm, Argo CD) who has handled CI/CD reliability issues with automated pre-deploy checks and rollbacks, and supported major migrations (on-prem to AWS; VM to EKS) with blue-green cutover planning.”

“QA automation engineer with Barclays digital banking experience who owned an end-to-end regression suite across UI, API, and database layers (Selenium/TestNG, REST Assured, SQL) and integrated it into CI/CD (Jenkins/GitLab). Known for preventing high-impact financial defects like duplicate transaction postings by adding backend SQL validations, negative/edge-case coverage, and converting production issues into automated regression tests; also strong in Cypress flake reduction using cy.intercept/cy.session and stable selectors.”

“Full-stack engineer who has shipped and owned production analytics dashboards using Next.js App Router + TypeScript, combining server components for data-heavy pages with client components for interactive charts/filters. Also built a Temporal-orchestrated payment reconciliation workflow with versioning, idempotency, and exponential-backoff retries, and has hands-on Postgres query/index optimization using EXPLAIN ANALYZE.”

Luis Aragon

Screened

Senior Software Engineer specializing in data infrastructure and distributed systems

San Francisco, CA6y exp

“Software engineer working on agentic AI SMS customer engagement flows and a Customer Data Profile service that unifies journey data across SMS/web/calls while enforcing precise consent management. Has hands-on production operations experience, including recovering a reporting-critical Elasticsearch outage by standing up a new cluster in Kubernetes, restoring from snapshots, and rewinding Kafka consumers to reprocess missed data.”

“Data engineer focused on building reliable, production-grade pipelines and external data collection systems on AWS (S3/Lambda/SQS/Glue/EMR) using PySpark/SQL, serving curated datasets to Snowflake/Redshift for finance and fraud teams. Has operated a large-scale crawler ingesting millions of records/day with anti-bot tactics, schema versioning/quarantine, and CloudWatch/Datadog monitoring, and also shipped a versioned REST API with caching and query optimization.”

“Built and productionized LLM-driven content intelligence/SEO agents for a high-traffic media platform, automating tagging/summarization/metadata with FastAPI + async orchestration and strict JSON-schema outputs. Demonstrated measurable impact (40% faster publishing, +20% organic traffic in 3 months) and strong reliability practices (offline evals, shadow mode, canaries, fallbacks, idempotency, and monitoring).”