Vetted Idempotency Professionals

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).”

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, cloud, and AI systems

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%+.”

Srilalitha Nanjangud Subbaswamy

Screened

Junior Software Engineer specializing in cloud-native backend and AI systems

Bangalore, India2y exp

“Early-career software engineer with experience at Cognizant and hands-on ownership of both enterprise backend systems and production LLM workflows. Built an internal certificate monitoring platform to reduce outage risk, and separately shipped a personalized news summarization/recommendation system that cut reading time by 60% and improved CTR@10 by 22%.”

“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.”

Harika Reddymalle

Screened

Mid-Level Full-Stack Software Engineer specializing in backend automation and insurance systems

Dallas, TX4y exp

“Full-stack engineer with hands-on production ownership across Angular/.NET/SQL and React+TypeScript/Node/Postgres stacks, including CI/CD and AWS operations (EC2/ECS, RDS, S3, CloudWatch). Delivered an internal insurance document upload and tracking feature end-to-end, adding audit/history and async processing, then validated success through monitoring metrics and reduced support tickets. Comfortable shipping MVPs in ambiguous environments using feature flags, strong validation, and backward-compatible database migrations.”

Sanjana Akula

Screened

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

New York, NY5y exp

“Front-end engineer with experience at Optum and Wells Fargo maintaining internal React/Angular component libraries and design-system-aligned UI modules used across multiple apps. Known for stabilizing shared libraries via semantic versioning, Jest test automation, and high-quality documentation, plus measurable performance wins (≈40% faster dashboard loads) through profiling-driven React and API optimizations.”

Sivapriya Rachakonda

Screened

Mid-Level Software Engineer specializing in cloud-native microservices on AWS and Kubernetes

Remote, USA5y exp

“Backend engineer who built a stateless Python/Flask service supporting a healthcare-document ETL pipeline, offloading heavy processing to Celery workers and adding strong observability (metrics, structured logs, audits). Demonstrates practical performance/reliability work: batch chunking, priority queues, autoscaling by queue depth/CPU, DLQ routing, and PostgreSQL tuning (indexes, pagination) to cut slow API responses. Also has experience deploying real-time ML classification via TensorFlow Serving behind a FastAPI wrapper and integrating models via REST/gRPC.”

“Built a production LLM-assisted workflow for customer configuration data migrations, combining agentic parsing with deterministic validation and fail-safe pipeline design. Stands out for turning messy ERP and operational data into reliable, repeatable transformations while improving accuracy and cutting manual effort by more than 80%.”

“Backend/data engineer focused on high-scale, event-driven AWS ingestion systems (SQS/Lambda/EKS) processing millions of events per day, with strong reliability patterns (idempotency, DLQs, bounded retries) and deep observability using Datadog distributed tracing. Has delivered Terraform/GitHub Actions CI/CD and improved secret rotation via Secrets Manager + IRSA, plus Glue-based ETL with schema-evolution handling and Postgres SQL optimization (including JSONB/GIN indexing). Candidate is currently living outside the US and states they do not have US work authorization.”

“LLM/RAG practitioner building clinician-facing AI search and Q&A inside EHR workflows, focused on trust, latency, and safety (grounded answers with citations, PHI controls, encryption/audit logs). Demonstrated real-time incident response for production LLM systems (e.g., fixing a metadata-filter deployment regression to prevent irrelevant results/cross-patient leakage) and strong demo/enablement skills for mixed technical and clinical stakeholders; also shipped a multi-model RAG tool at OrbeX Labs with upload/search/audit features for day-to-day adoption.”

“Systems Engineer at Tata Consultancy Services with hands-on ownership of enterprise logistics microservices (Spring Boot) using Kafka integrated with Azure Event Hubs, including partitioning strategies and operational handling of consumer lag/duplicate events. Also built a full-stack road-accident blackspot detection application using Python-based spatial clustering and model evaluation with a JavaScript/Mapbox frontend.”