Vetted Idempotency Professionals

“Backend engineer who has shipped both high-throughput real-time systems and production LLM/RAG features. Built a database-free, local-first messaging service (Node/Express/Socket.IO) achieving ~1,500 msgs/sec at <25ms p95, and implemented a Go-based RAG recommendation pipeline with strict JSON/schema validation, catalog grounding, fallbacks, and eval loops that cut hallucinations to ~1–2% while reducing LLM costs ~60%.”

“Built and operated a real-time student event/party discovery platform with map-based search, RSVP, and authentication using React/TypeScript, Node.js, and Firebase Firestore. Demonstrates strong backend correctness under concurrency (transactions, idempotency, retries/backoff) and solid API product thinking (versioning, Swagger docs, structured errors, cursor pagination), including custom geospatial querying via Haversine filtering.”

“Backend/platform engineer with Optum experience owning a production FHIR Member Access API aligned to CMS interoperability requirements. Built and scaled Spring Boot/HAPI FHIR microservices on AWS (Docker/Kubernetes) with zero-downtime CI/CD, and operated them with strong observability (Dynatrace, logs/metrics, alerting) and incident response. Also implemented a Kafka-based FHIR bulk data pipeline with schema versioning, idempotent processing, and reliable backfills/replays.”

Srichandan Kota

Screened

Senior Full-Stack AI Engineer specializing in Generative AI and FinTech

Minneapolis, MN6y exp

“Backend engineer who built and owned an AI-powered financial research product end-to-end, using a typed NestJS/GraphQL backend with LangGraph-style agent routing to produce sourced, structured financial analysis. Emphasizes finance-grade correctness (Zod validation, metric registries, unit/empty-result guardrails) while keeping latency low via batching, caching, and fast token streaming, and has led incremental migrations using strangler/feature-flag/shadow traffic patterns.”

Israel Sodano

Screened

Principal/Staff Software Engineer specializing in distributed systems and FinTech platforms

São Paulo, Brazil13y exp

“Brazil-based tech leader who helped build Bankly’s end-to-end Banking-as-a-Service platform—delivering a plug-and-play solution in 6 months and architecting for ~5k requests/second; Bankly later became the largest BaaS in Brazil. Also runs a closed, personal-capital private trading group focused on automating investment decisions with AI trading bots, but is currently prioritizing international career growth over entrepreneurship.”

Veena Vyshnavi Garre

Screened

Senior Full-Stack Software Engineer specializing in cloud-native systems and AI/ML

Hyderabad, India7y exp

“Backend engineer who significantly evolved an internal Resource Manager platform, moving from a monolith to microservices and improving onboarding speed while reducing integration errors. Has hands-on experience building reliable and secure Python/FastAPI APIs (Pydantic schemas, circuit breakers, caching, metrics/alerts) and leading zero-downtime migrations with strong data integrity patterns (dual writes, idempotency, reconciliation checks).”

Sumanth Gottipati

Screened

Mid-level Full-Stack Software Engineer specializing in cloud-native microservices and FinTech

New York, NY4y exp

“At Delta Airlines, built and shipped a production LLM-powered semantic search/troubleshooting assistant over maintenance logs and operational documentation using OpenAI embeddings and a vector database. Implemented hybrid ranking, query enrichment, and structured filters to improve relevance ~35% while optimizing latency via caching and vector tuning. Also designed a scalable Kafka + AWS (Lambda/SQS) ingestion pipeline with strong reliability/observability and an eval loop using real engineer queries and human review.”

EMMANUEL ETIENNE

Screened

Engineering Manager specializing in FinTech money movement and AI-driven infrastructure

Brooklyn, NY12y exp

“Player-coach fintech engineer/engineering lead who built a deterministic payer-ID wire reconciliation system with Citi, including idempotent ingestion and webhook processing across Ruby and Go, materially reducing accounting manual work. Experienced in incident response (Plaid-related customer-impacting issue), stakeholder-driven MVP scoping for ACH status visibility, and delivery acceleration via infrastructure templating (EC2) and standardized Magento project setups.”

Alankrit Srivastava

Screened

Intern Data Engineer specializing in Snowflake pipelines and AI/ML analytics

Houston, TX3y exp

“Built and operated an end-to-end TypeScript/Node AI agent platform for high-volume financial data that generates explainable investment signals and automates execution via resilient Playwright browser automation. Uses Postgres + pgvector/Prisma for RAG retrieval, Redis for async orchestration, Zod-based boundary validation as a circuit breaker, and OpenTelemetry for tracing/latency monitoring; also designed a TypeScript SDK with semver, scoped bearer-token auth, CLI key rotation, and interactive Swagger docs.”

Ramya Sree Kanijam

Screened

Mid-level Software Engineer specializing in backend systems, cloud, and AI pipelines

Remote, USA3y exp

“Built and owned an end-to-end AI-driven content enrichment pipeline for a news workflow, using n8n, LLM agents, and external APIs to automate ingestion, deduplication, categorization, and approval routing. Stands out for production-minded AI systems work: they improved reliability with schema validation, retries, idempotency, and monitoring, while automating 90% of processing and cutting duplication errors by 95%+.”

Julian Thong

Screened

Senior Software Engineer specializing in FinTech platforms

San Francisco, CA4y exp

“Senior software engineer with deep experience in private markets platforms, spanning full-stack product development and complex backend modernization. Notably helped migrate a core IOI processing system from a Rails monolith to .NET microservices with Kafka-based event sequencing, and contributed to an Offerings platform that drove 50% faster transactions for investors and operations teams.”

Dinesh Guguloth

Screened

Mid-level Software Engineer specializing in full-stack cloud-native applications

New York, NY4y exp

“Full-stack engineer with cloud and GenAI experience who has owned production features end-to-end, including a reporting dashboard optimized from 14s to 5s using query/API refactoring and monitored via AWS CloudWatch. Also productionized an OpenAI-powered chatbot using LangChain with prompt design, guardrails, and evaluation via production logs and user feedback, and has led incremental legacy-to-microservices modernization with parallel run to avoid regressions.”

“Built and evolved the backend-adjacent platform for a self-custody Bitcoin wallet used by 2000+ users, emphasizing security-first architecture that avoids custodial risk by keeping private key operations client-side. Demonstrates strong API reliability and security depth (FastAPI contract-first design, idempotency, state-machine modeling, JWT/device-aware auth) and has reduced production failures by hardening signing flows against poor connectivity.”

“Backend/data engineer with production experience building Python FastAPI services and AWS-native data pipelines. Has delivered containerized and serverless workloads (ECS/EKS/Lambda) with Terraform-based IaC, strong reliability patterns (JWT/RBAC, retries/circuit breakers, observability), and AWS Glue ETL into S3/Redshift. Demonstrated measurable SQL performance wins (40–50s to <4s) and owned real pipeline incidents through detection, mitigation, and prevention.”

“AI Backend Engineer in MetLife’s claims technology group who built and deployed a production LLM-based decision support system that helps claim adjusters quickly find relevant policy rules from long PDFs and historical notes. Designed it as multiple production-grade services with retrieval-first guardrails, continuous validation, and Airflow-orchestrated pipelines for ingestion, embeddings, and vector index updates to keep the system reliable as policies and data evolve.”

“Built and deployed an LLM/applied-ML system enabling efficient extraction of useful information from large unstructured multimodal datasets, owning the full pipeline from ingestion to inference and APIs with a strong emphasis on production reliability, latency, and monitoring. Also delivered a voice-based AI workflow for Hindi policy document access for the Election Commission of India by translating non-technical usability needs into iterative demos and a successful implementation.”

“LLM/agent builder who shipped a live consumer AI-agent app (kalpa.chat) that visualizes complex reasoning as interactive graphs and abstracts multi-provider model usage via a unified wallet. Professionally has applied LangChain/LangGraph to IVR parsing and to scaling a football video-generation pipeline at DAZN, including shipping a VAR-specific retrieval/order fix via SQL after iterating with a non-technical PM.”

“Built and owned end-to-end TypeScript/React dashboards with a Node.js backend, including post-launch additions like role-based access and new reporting views enabled by modular architecture and clean API boundaries. Also created an internal real-time operations/engineering dashboard that replaced spreadsheets and reduced manual tracking, iterating quickly based on direct team feedback.”

“Full-stack engineer with ~20 years of experience (including 5–6 years in consultancy) who has shipped and operated production systems across a wide range of stacks. Recently owned an end-to-end receipts feature integrating Stripe, generating PDFs, and sending HTML emails, deployed via GitHub Flow to AWS ECS; handled real-world performance issues (oversized merchant images) with compression and server tuning.”

“Built and launched “Language AI,” a Next.js/TypeScript app that clones a user’s voice (via ElevenLabs) to deliver language lessons in their own voice, using Supabase for auth/Postgres/storage and hosting backend on Render. Post-launch, identified ElevenLabs voice-clone limits after initial users and reworked the pipeline to store audio assets and delete clones to support more concurrent users; also added Google auth to improve adoption. Previously worked in a high-growth startup environment (Study Park) taking concepts from ideation to production.”

Filmon Tesfay

Screened

Senior Full-Stack Developer specializing in cloud-native FinTech and AI platforms

New York, NY8y exp

“Full-stack engineer with strong production ownership: built and operated a real-time transaction monitoring/fraud-alerting system using Java Spring Boot, Kafka, Docker, and AWS with CI/CD. Demonstrates metrics-driven operations (latency, stability, consumer lag, true/false positives) and reliability patterns for integrations (idempotency, retries/backoff, DLQs, reconciliation/backfills), plus modern React/TypeScript + Node/Postgres architecture experience.”

Shivam Lahoti

Screened

Junior Full-Stack Software Engineer specializing in TypeScript/React and microservices

Boston, USA2y exp

“Software engineer who built and owned an internal workflow automation + analytics platform end-to-end (TypeScript/React/Node) with a microservices, RabbitMQ-based async architecture. Drove adoption by shipping iterative prototypes and prioritizing reliability/performance (Redis caching, query optimization), delivering ~30–35% latency improvements and ~30–40% reduction in manual operational work.”

Bhoomi Parikh

Screened

Junior Product Manager specializing in AI-enabled analytics products

Mountain View, CA2y exp

“Product/full-stack engineer with analytics-dashboard experience at Kantar, owning features end-to-end from React/Next.js UI through Postgres data modeling and query optimization. Built a multidimensional filters/tags module that cut analyst discovery time by ~60% and also implemented durable backend workflows for bulk report generation with retries and idempotency, validated via EXPLAIN ANALYZE and production monitoring.”