Vetted Postman Professionals

“Backend/platform engineer who owns policy-lifecycle workflow microservices built in Python/FastAPI with async + DDD, Kafka event processing, SQLAlchemy, JWT/RBAC, and Redis caching (cut DB load ~40%). Experienced deploying Java and Python microservices to Kubernetes with Helm and GitOps (ArgoCD) plus Jenkins/GitHub Actions pipelines to AWS/ECR, and has supported phased on-prem-to-cloud migrations with dependency mapping and data consistency strategies.”

“AI/ML engineer who has deployed transformer-based NLP systems to production via Python REST APIs and Kubernetes on AWS/Azure, with a strong focus on latency optimization (p95), reliability, and scalable orchestration. Demonstrates pragmatic model tradeoff decision-making and strong stakeholder collaboration—improving adoption by making outputs more actionable with summaries, extracted fields, and confidence indicators.”

“Backend engineer working on high-volume insurance claims intake systems who shipped a production GenAI document-classification capability in Spring Boot microservices. Emphasizes reliability in LLM systems (strict schemas, confidence thresholds, monitoring, and manual-review fallbacks) and runs evaluation loops with labeled historical documents to drive prompt/validation improvements and reduce manual review.”

“Cloud/DevOps engineer (6+ years) with healthcare domain experience who has owned production AWS systems end-to-end—building real-time data pipelines and an admission forecasting ML service delivered via API and Tableau. Led EMR modernization from on-prem/VMs to containerized AWS using phased migration and blue-green deployments, achieving ~99.5% uptime while cutting on-prem footprint ~30% and driving major automation gains (up to ~90% manual work reduction).”

“Backend engineer (Marsh McLennan) who evolved a high-volume claims automation pipeline in Python, emphasizing thin APIs with background job processing, strong validation/retries, and production-grade observability. Experienced in secure FastAPI API design (centralized JWT/RBAC), multi-tenant Postgres/Supabase-style row-level security, and low-risk refactors using parallel runs and feature flags; targeting founding-engineer scope roles.”

“QA professional focused on CRM workflow and case management releases, owning end-to-end validation from staging through release readiness. Demonstrated ability to catch critical UI-to-backend mapping defects early using API/DB validation and audit logs, then prevent recurrence by adding automated edge-case tests into CI.”

Apurva Banka

Screened

Mid-level Full-Stack & AI Engineer specializing in cloud, data platforms, and LLM automation

Houston, TX5y exp

“Software engineer/product builder who has owned an agentic affiliate lead-gen platform end-to-end (Django + React/TypeScript) and deployed it on Kubernetes in anticipation of 10x user growth from ~5K DAUs. Also has healthcare claims microservices experience using Kafka, including hands-on performance tuning to address consumer lag and broker pressure, and built an internal downtime alerting tool adopted across the organization.”

Vedang Jadhav

Screened

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

New York City, NY5y exp

“Backend engineer with experience across healthcare and fintech platforms (Anthem, Citia) building high-throughput Python microservices with strong compliance/security focus (HIPAA, tenant isolation). Has integrated ML workflows into production systems (ResNet embedding-based image similarity) using async pipelines (Celery/Redis) and AWS (Lambda/S3/ECS), delivering measurable performance and fraud/content-integrity improvements at scale.”

Sharanya Rao

Screened

Mid-level AI/ML Engineer specializing in NLP, LLMs, and RAG for finance and healthcare

Remote, USA3y exp

“Built an AI lending assistant (RAG + DeBERTa) used by credit analysts to retrieve policies and past loan decisions, tackling real production issues like hallucinations, document quality, and sub-second latency. Deployed a modular, Dockerized AWS architecture (ECS/EMR + load balancer) with load testing, caching/precomputed embeddings, and CloudWatch monitoring, and used Airflow to automate scheduled data/embedding/vector DB refresh pipelines with retries and alerts.”

Tina Nguyen

Screened

Mid-Level Software Engineer specializing in iOS and full-stack development

Sunnyvale, CA3y exp

“Cross-platform (web + mobile) product engineer working on coupon clipping experiences. Built and shipped category-based filtering informed by external market data (Rakuten/Honey) and internal user-journey analytics, validated via A/B testing and resulting in a 30% traffic lift. Experienced handling on-call production incidents, including rapid root-cause analysis and hotfixing a mobile crash that was blocking a release.”

RAJ KUMAR

Screened

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

Chicago, IL6y exp

“Backend engineer at Discover who built and scaled Python/Flask services for a card dispute resolution platform, tackling long-running external network validations with Celery+Redis and delivering measurable gains (response time ~3s to <300ms; throughput +40%). Experienced in high-scale PostgreSQL/SQLAlchemy optimization (partitioning, read replicas, N+1 avoidance), event-driven systems with Kafka, and integrating ML fraud detection using AWS SageMaker/Lambda/ECS with clear separation of real-time vs batch processing.”

Pravalika Badam

Screened

Mid-level QA/SDET Automation Tester specializing in UI, API, mobile, and cloud testing

Houston, TX5y exp

“SDET focused on end-to-end quality for web applications, owning UI/API/regression automation from framework design through CI/CD integration. Notably prevented a production payment/checkout incident by adding API validations that caught incorrect tax calculations (rounding logic) during CI before release, and has a track record of stabilizing flaky Cypress tests via robust selector and wait strategies.”

Venkat Palaparthi

Screened

Senior Software Engineer specializing in cloud-native microservices and secure enterprise platforms

Dallas, TX6y exp

“Full-stack engineer with strong production ownership in banking/identity & entitlements systems, building Spring Boot + Postgres/Redis services and React dashboards, then deploying on AWS EKS with Jenkins CI/CD. Demonstrated impact through reduced authorization latency and fewer access-related support tickets, plus strong observability and reliability practices (CloudWatch, tracing, autoscaling, Kafka pipelines with DLQs and reconciliation).”

Ali Taquie

Screened

Junior Software Engineer specializing in AI and FinTech payments

Santa Cruz, CA2y exp

“Forward-deployed software engineer at PayStand who uses LLM prototyping tools (e.g., Cursor, Lovable) to rapidly build customer-specific demo environments and drive sales outcomes—citing ~$100K in technical buy-in before production development. Experienced supporting an enterprise expense management product (Teampay) with agentic AI workflows, emphasizing observability (Grafana/Loki/Tempo) and cross-functional communication with sales, product, developers, and customers.”

Abhishek Saraswat

Screened

Mid-level Software Engineer specializing in Java backend microservices

Arlington, TX4y exp

“Backend/distributed-systems engineer focused on automation and near-real-time processing, building Java/Spring Boot microservices with Kafka, PostgreSQL, and AWS. Strong in scaling and reliability work—debugging tricky asynchronous messaging issues (delays, duplicates, out-of-order events) and improving resilience/observability with retries, fallbacks, logging, and monitoring. No production ROS/ROS2 experience yet, but has studied core ROS concepts and draws clear parallels to event-driven architectures.”

“Data-focused engineer who has built near real-time trending news sentiment pipelines end-to-end (API/web ingestion, validation, transformations, and dashboard serving) and implemented reliability patterns like retries with exponential backoff and backfills. Also shipped Java/Spring Boot REST APIs backed by SQL with indexing/pagination, and stood up an early-stage QR-based attendance MVP using Firebase with iterative hardening via logging and validation.”

Robert Wheeler

Screened

Executive Technology Leader (CTO) specializing in cloud, AI/ML, and scalable product platforms

Manhattan, USA25y exp

“Technical leader and hands-on engineer with 20+ years of experience who has previously raised funding and exited a venture. Currently bootstrapping a new AI-direction startup with personal and family capital, leveraging structured financial planning and a relationship-driven approach to investor outreach.”

“Full-stack engineer with end-to-end ownership of a production customer plan activation and account management flow at T-Mobile, spanning Java/Spring Boot APIs, React frontend, and Docker-based CI/CD deployments. Demonstrated performance/scalability work (query optimization, indexing, caching) and measured success via improved retrieval speed and reduced support tickets.”

Pratik Patil

Screened

Senior Frontend Engineer specializing in React and FinTech SaaS

New York, NY6y exp

“Senior engineer at BDI Plus who is already using AI coding tools as a core part of daily development, with hands-on experience building enterprise LLM products such as ChatCDP AI for Morgan Stanley analysts. Particularly strong at making AI systems trustworthy and usable through auditable outputs, streaming UX, and resilient state-machine-driven error handling.”

Harika M

Screened

Mid-level Full-Stack Developer specializing in FinTech and enterprise platforms

Plano, TX6y exp

“Engineer with a pragmatic, production-focused approach to AI-assisted development, using tools like Copilot and ChatGPT to accelerate coding while maintaining strict validation for correctness, security, and performance. Particularly notable for building a multi-agent incident-resolution workflow for a financial platform, with specialized agents for log analysis, root cause identification, fix suggestions, and test generation.”

“DevOps- and infrastructure-focused engineer who is already applying AI in practical delivery workflows, including Terraform, CI/CD, Kubernetes, and multi-agent automation. Stands out for combining AI-driven productivity with disciplined validation through testing, code review, and security checks, and for leading cross-functional AI integration across development, QA, and infrastructure.”

“ML engineer at CGI who built demand forecasting models end-to-end, from feature engineering and training through AWS deployment. Stands out for a production-first mindset and strong skepticism of AI-generated code, including catching a Copilot-generated SQL query that would have caused a costly full table scan in production.”

“Built an itinerary-planning startup MVP (LessGO) using React/TypeScript and a Node/Express backend integrating Google Maps and Gemini AI. Notably optimized Gemini latency from ~40 seconds to ~3 seconds through frontend caching, debugging, and model selection, and has TA experience supporting others with deployments and database connectivity.”