Vetted GraphQL Professionals

“Full-stack product engineer who owned a live-events digital ticketing platform end-to-end, including blockchain-based ticket validation and high-traffic booking flows. Stands out for combining Angular/React frontend work with Java/Spring Boot backend architecture, plus strong production reliability practices around concurrency control, queues, observability, and UX optimization.”

“Backend engineer who replaced an Excel-heavy forecasting workflow with a secure, auditable FastAPI system (React UI + relational model + async workers), emphasizing deterministic processing, idempotency, and versioned ledger-style ingestion. Led a monolith-to-FastAPI migration at Bounteous using a strangler approach, feature-flagged incremental rollout, and data reconciliation/shadow-compare to protect integrity while scaling onboarding workflows.”

“Built and productionized an LLM-driven document verification workflow for a construction firm’s submittals process, moving from a Vercel/Next.js prototype to a FastAPI + LangChain/LangGraph backend with background workers and multi-server deployment. Uses LLM tools (e.g., OpenAI Codex/Cloud Code) for rapid development and log-driven root cause analysis, and partners with customer teams on evaluation metrics and iterative improvements.”

Lavrenti DeLavrenti

Screened ReferencesStrong rec.

Director-level Technology Leader specializing in cloud-native platforms, AI/ML, and SaaS

Remote15y exp

“Engineering leader (Director/VP level) who has repeatedly aligned product and engineering through ROI-driven quarterly roadmaps and strong stakeholder communication, including board presentations. Built a parallel cloud team to migrate an on-prem product to the cloud, credited with delivering $9M ARR, and led a Python monolith-to-serverless event-driven microservices transformation. Currently manages distributed teams across Mexico, India, and the US using pod-based structures, clear KPIs, and a supportive accountability culture.”

suparshwa patil

Screened ReferencesStrong rec.

Mid-level Software Engineer specializing in AI platforms and full-stack systems

Santa Clara, CA4y exp

“Built and shipped a production AI-powered Q&A/RAG onboarding assistant at One Community Global that unified knowledge across Notion, Google Docs, and Slack, cutting volunteer onboarding time by 45%. Demonstrates strong end-to-end ownership: LangChain agent orchestration integrated into a FastAPI backend, rigorous evaluation (200-query dataset, ~85% accuracy), and production feedback/monitoring with source-attributed answers to build user trust.”

“Backend engineer currently at Citigroup working on real-time transaction processing systems with Kafka. Stands out for using AI tools pragmatically in a regulated banking environment to improve debugging, testing, and developer productivity while keeping human control over architecture, security, and performance decisions.”

“Full-stack engineer/product owner who built and scaled a customer-facing job application portal (Skillbridge) using TypeScript/React and Spring Boot/MongoDB, optimizing search performance with indexing, caching (Redis), and payload/lazy-loading improvements. Also built an internal AI-driven analytics dashboard for Salesforce operations using OpenAI sentiment analysis, achieving 70% reduction in manual analysis and driving adoption through demos and iterative feedback.”

“Full-stack engineer who built and owned an internal analytics dashboard for sales (React/TypeScript + Node/Express + NoSQL), delivering it two weeks early with zero production issues and a reported 10% sales-efficiency lift. Experienced with microservices and async messaging patterns (retries/DLQs/idempotency), and emphasizes rapid iteration with strong CI/CD and automated testing plus user-driven adoption.”

“Cloud-native integration engineer (Oracle/OCI) with strong production deployment and incident-response experience, including API gateway rollouts, observability (Prometheus/Grafana), and multi-layer debugging for payments systems. Built Python/FastAPI microservices and automation for customer-specific reporting and data sync, and has delivered major performance gains (45 min to <10) plus reliability improvements (MTTD reduced 40%+) through monitoring, playbooks, and resilient integration patterns (streaming/queuing, retries, secure tokens, VPC peering).”

“Backend engineer at Cerebrone.ai building cloud-native Flask microservices for an AI-driven automation platform on GCP (Cloud Run/App Engine), including dedicated inference services integrating OpenAI and internal ML pipelines. Demonstrated strong performance and scalability wins across Postgres/SQLAlchemy optimization, multi-tenant (healthcare/HIPAA-grade) data isolation, and high-throughput background processing with Celery/Redis/RabbitMQ, with multiple quantified latency/CPU/throughput improvements.”

“Customer-support/engineering background spanning Informatica PowerCenter ETL and IBM demos/workshops, with hands-on experience hardening data workflows for production (error tables/reject links, validation, restart strategies, alerting, performance tuning). Also demonstrates a clear, systems-level approach to diagnosing LLM/agentic workflow issues (prompt/RAG/tooling/memory) using instrumentation and iterative fixes, and has partnered with sales on POCs by defining success metrics and mapping solutions to customer architectures.”

“Full-stack engineer with strong production ownership across SDK tooling, APIs, and operations. At Statsig, built real-time SDK diagnostics spanning 16 SDKs and improved incident response (40% faster mitigation) with Datadog SLOs/alerting; also shipped an enterprise Console API + interactive OpenAPI-based docs with robust versioning/migration practices. Has early-stage startup experience at Layup Parts, translating AS-9100 compliance needs into production workflows under rapidly changing requirements.”

“Deloitte engineer who built and shipped AI-powered, Kafka-driven workflow automation for transportation/document processing, including LLM-based semantic search. Strong in production reliability (idempotency, offset management, retries), observability (Datadog/CloudWatch), and database performance tuning (PostgreSQL/Flyway), with measurable latency improvements.”

“Backend-leaning full-stack engineer with production experience in both healthcare (claims enrichment/interoperability at Abacus) and finance (Goldman Sachs pricing/risk APIs + React dashboards). Built an event-driven AI grading platform using Postgres Debezium CDC + Kafka + FastAPI on AWS that cut manual grading ~70% and served 1000+ students, with strong emphasis on reliability, testing, and performance tuning.”

“Internship at ActiveVM where they tackled large-scale Spring Boot 2→3/library migrations across hundreds of downstream products by combining OpenRewrite (AST-based recipes) with an LLM/RAG-based classifier that routed risky files to human experts. Reported ~70% reduction in manual effort and 90%+ accuracy after testing across multiple branches and cutovers; also built a CTR-driven book recommendation capstone showcased at the Google office in Cambridge.”