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Vetted Postman Professionals
Pre-screened and vetted.
Shivoham Angal
Entry-level Backend Software Engineer specializing in AI and cloud systems
“Backend-focused engineer who built a hackathon trading vault (AntiSwan) integrating the Polymarket CLOB client and applying the Kelly Criterion for allocation decisions. In an internship at StartupU, owned pre-launch monitoring by building Azure dashboards and Terraform/KQL-driven alerts with Microsoft Teams webhook routing, and previously automated a DynamoDB cross-region migration with integrity checks.”
Jeff Craven
Director-level delivery executive specializing in enterprise SaaS, telecom, and platform deployments
“Enterprise SaaS implementation leader with broad cross-functional ownership spanning project management, sales engineering, customer success, and technical account management. Has delivered complex migrations and multi-release portfolios across 40+ enterprise customers, including utilities, telecom, and municipal environments, with strong experience coordinating high-stakes cutovers, integrations, and executive stakeholder communication.”
Cassandra Pizarro
Mid-level Software Engineer specializing in frontend and integrations
“Frontend-leaning product engineer with strong ownership in fintech integrations, including leading the first global PayPal integration on QuickBooks and enabling 20,000+ non-U.S. users across UK, Canada, and Australia. Brings a mix of React/TypeScript architecture, API collaboration, and domain depth in accounting workflows like VAT and Chart of Accounts mapping.”
Krishna Lella
Mid-level Software Engineer specializing in full-stack FinTech systems
“Backend-leaning full-stack engineer with PayPal experience building payment orchestration, settlement, and merchant risk systems at production scale. Stands out for combining cloud-native AWS delivery, database/query performance tuning, and reliability work in event-driven microservices, including a monolith-to-microservices migration that doubled deployment frequency and cut incident response time by 40%.”
Manoj Shinde
Senior Full-Stack Engineer specializing in cloud-native AI and FinTech systems
“Full-stack engineer who has owned customer-facing reporting products end to end and also helped ship MemberGPT, an AI assistant for financial users. Brings a practical mix of React/TypeScript and Java/Spring Boot experience, plus hands-on LLM integration, retrieval grounding, evaluation, and production monitoring in a higher-trust financial context.”
Tejaswi Reddy Jaidi
Mid-level .NET Full-Stack Developer specializing in Azure and enterprise web apps
“JavaScript engineer with hands-on experience improving performance in data-heavy table UIs (thousands of rows), including an open-source DataTables extension fix that reduced redundant AJAX calls via debouncing and was merged upstream. Comfortable profiling/benchmarking, optimizing DOM and network behavior, and collaborating with OSS maintainers through GitHub issues/PRs while also producing clear developer documentation and quick-start examples.”
Sukeshini Ayendla
Mid-level Full-Stack .NET Developer specializing in cloud-native microservices
“Full-stack engineer with primary depth in .NET Core and Python who has built and deployed end-to-end AWS applications (Lambda, API Gateway, S3, CloudFront) and supported them in production. Experienced in scaling large, data-driven workloads using queues/background workers, batching, and database tuning, with strong focus on API contracts, observability, and resilience patterns; also has hands-on React/TypeScript and some Spring Boot exposure.”
Ketul Gandhi
Senior Backend Software Engineer specializing in FinTech and AWS microservices
“Engineering leader/CTO-type with deep experience building and scaling a vehicle routing platform at Transdev On Demand, including a nationwide rollout to 22 US airports ahead of schedule. Drove engineering best practices (CI/CD, high test coverage, pair programming, automated deployments) and led a multi-tenant architectural upgrade to expand the routing engine to additional business lines and external customers.”
Sai Aditya Paruchuri
Mid-level Software Engineer specializing in cloud-native microservices and AI-powered web applications
“Backend engineer who built and owned an AI-powered SMS survey platform for a nonprofit serving at-risk communities (internet-limited users), using Cloudflare Workers + Twilio and a state-machine survey engine. Scaled it to ~10k active users with near-zero downtime, added English/Spanish support, and iteratively improved LLM behavior (Claude 3.7 Sonnet) to handle nuanced, real-world SMS responses reliably.”
Achyuth Kummari
Mid-Level Full-Stack Software Developer specializing in Java/Spring, React, and AWS
“Full-stack engineer with end-to-end ownership experience, including building a real-time campaign/inventory dashboard at P&G using React/TypeScript, Spring Boot, GraphQL/REST, Redis, Docker, and AWS (EC2/RDS/S3) with Prometheus/Grafana observability. Demonstrates strong performance and reliability focus (p95 tuning, caching, idempotent event-driven ingestion with DLQs/reconciliation) and has shipped MVPs in ambiguous early-stage environments.”
Suresh Kunchala
Mid-level Full-Stack Developer specializing in FinTech and enterprise web platforms
“Financial-services AI engineer who shipped a production investment research assistant using RAG over internal research reports, SEC filings, and meeting transcripts, with a strong emphasis on truthfulness and guardrails. Built a structured evaluation loop (200+ golden test cases, RAG Triad metrics) that directly improved retrieval quality (e.g., fixing year-mismatch retrieval, boosting sensitive-query performance by 18% and cutting hallucinations to near zero) and scaled ingestion to ~10k messy documents with RabbitMQ + OpenTelemetry.”
Palash Gharde
Mid-level Software Development Engineer specializing in backend, data engineering, and ML systems
“ML/Backend engineer with ServiceNow experience building production-grade inference services on FastAPI with Docker/Kubernetes (autoscaling, health checks) and strong reliability practices (monitoring, retries/timeouts, fallbacks). Delivered measurable improvements including 30% lower API latency and 18% higher model accuracy, and built A/B testing plus drift-triggered retraining loops to keep models stable in production.”
Srinivas Matta
Mid-Level Full-Stack Software Developer specializing in cloud-native web platforms
“Software engineer at Capital One who owned and shipped AI-driven personalization and internal insights dashboards end-to-end, emphasizing fast iteration with feature flags and tight user feedback loops. Built a TypeScript/React + Spring Boot/Python document automation platform with compute-heavy NLP microservices, async workflows, and production-scale reliability/performance practices (Kafka/RabbitMQ-style queues, Redis caching, tracing).”
John Chen
Junior Full-Stack & Data Scientist specializing in ML/NLP and analytics products
“Built and deployed profitprops.io, a sports betting player-props prediction product using ML/AI. Implemented backend APIs with FastAPI/Express.js and Supabase, trained models on AWS GPU (P3) using Docker + RAPIDS, and set up CI/CD with GitHub Actions while working around cost constraints and data-collection hurdles (EC2 proxy rotation/rate limits).”
Sayali Patil
Mid-level Python Full-Stack Developer specializing in Healthcare and FinTech
“Backend engineer with hands-on experience building a fraud-transaction monitoring system in Python/Flask, architected as Dockerized microservices and integrated with Kafka for high-volume streaming. Demonstrates strong performance and reliability chops across PostgreSQL/SQLAlchemy tuning (EXPLAIN ANALYZE, N+1 fixes, bulk ops), multi-tenant data isolation, and scaling via background workers + Redis caching, plus real-time ML inference deployment using TensorFlow on AWS.”
Joseph Herbst
Executive Technology Leader specializing in IoT, PoE building automation, and semiconductors
“Engineering/exec leader (CEO experience) who built a lighting controls and building automation platform from scratch, choosing an Ethernet/PoE and Node.js web-centric architecture that anticipated market shifts and later became an industry pattern. Known for rigorous vendor QA (test-to-failure) and for delivering high-profile deployments (e.g., Black Desert Resort, Resorts World Villa 66) while leading globally distributed engineering teams.”
Alexey Elkin
Junior Full-Stack Software Engineer specializing in cloud analytics and web applications
“LLM/agentic workflow engineer with hands-on experience turning demo-grade LLM analytics into production-ready features by tackling tail latency, observability, and cost/reliability controls. Strong at diagnosing real-time customer incidents via trace-driven debugging across retrieval, tool calls, retries, and prompt/version metadata, and frequently partners with sales as a technical lead to de-risk enterprise pilots through transparent failure-mode walkthroughs.”
Naga Manasa Bandaru
Mid-level Frontend Software Engineer specializing in React, Next.js, and TypeScript
“Product-focused full-stack engineer with FedEx experience building an internal logistics dashboard for near real-time shipment status and performance metrics using Next.js App Router + TypeScript. Strong in production ownership and performance work—uses React Profiler/Chrome DevTools to eliminate expensive re-renders and applies Postgres indexing/query tuning validated via EXPLAIN ANALYZE to improve dashboard responsiveness.”
NIDHEESH VELUTHERI
Senior Full-Stack Engineer specializing in modern web applications
“Frontend engineer with insurance-domain experience (AAA Insurance and insurance quoting flows) who has delivered Angular/React/Next.js products end-to-end. Notable for building a complex drag-and-drop email template/code-generation UI and for modernizing React codebases (Redux->Context, lazy loading, memoization) to improve performance and reduce security vulnerabilities, while using feature flags and strong QA automation for fast, controlled releases.”
Sankalp Tiwari
Mid-Level Software Engineer specializing in backend microservices and FinTech data pipelines
“Backend engineer at Goldman Sachs who built LLM-powered reconciliation/reporting services and high-throughput Kafka pipelines (8M+ events/day). Strong in production-grade Python/FastAPI microservices on Kubernetes with GitOps-style CI/CD, plus experience migrating legacy reporting/settlement services onto an internal Kubernetes platform using shadow deployments and gradual cutovers.”
Suloni Praveen
Entry-Level Software Engineer specializing in data engineering and ML systems
“Built an end-to-end Next.js/TypeScript LLM-based scientific PDF analyzer using local Ollama/Llama inference to prioritize privacy and cost, producing structured research artifacts (e.g., authors/methods/findings) with ~92% extraction accuracy. At Qualtrics, helped replace a batch pipeline with a real-time, low-latency ML inference service (Python/Go on Kubernetes) using Redis caching, Grafana-based observability, and graceful fallbacks to protect UX during failures.”
Atharva Bhide
Entry Software Engineer specializing in AI/ML and multimodal systems
“Built and shipped a production healthcare AI platform for a clinic in Brea, LA that combined LLM-based clinical report generation, voice agents for appointment workflows, and camera-based patient monitoring. Stands out for pairing multimodal AI architecture with production-grade reliability and compliance practices, while delivering concrete business results including 90% workflow automation, 200 hours saved per month, and a 60% improvement in customer retention.”
Chisom Osuji
Entry Backend Engineer specializing in distributed systems and APIs
“Early-career builder with hands-on project experience spanning Python data processing, a Chrome extension for autofilling job applications, and a sign-language glove system integrating sensors, microcontrollers, and a web interface. Stands out for approaching student and project work with a production-minded focus on validation, modularity, edge cases, and reliability.”
Josiah Aviles
Senior AI/ML Software Engineer specializing in Generative AI and RAG systems
“Built and owned Alight's AI-powered Search Summary feature end-to-end, using a RAG pipeline with OpenSearch and Bedrock, and drove a 20% increase in user feedback scores. Stands out for bringing rigorous production evaluation to LLM systems via live LLM-as-a-judge monitoring, and for experience with advanced agentic architectures, hybrid search, and reranking at scale.”