Vetted State Management Professionals

Pre-screened and vetted.

AN

Senior Full-Stack Engineer specializing in React and micro-frontends

New York, NY8y exp
Goldman SachsNYU
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CT

Intern Software Engineer specializing in full-stack web and AI agent development

Pittsburgh, PA0y exp
CMU Human-Computer Interaction InstituteCarnegie Mellon University
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RM

Mid-level Full-Stack Java Developer specializing in FinTech and Healthcare IT

5y exp
JPMorgan ChaseWright State University

Backend engineer with experience at JPMorgan Chase and Walgreens, owning transaction-processing and prescription data flow systems in regulated environments. Brings strong hands-on depth in Spring Boot microservices, Kafka, Redis, Kubernetes, observability, and production incident resolution, plus practical experience integrating OpenAI-powered workflows with validation and fallback safeguards.

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EA

Mid-level Full-Stack Software Engineer specializing in web platforms

Overland Park, KS4y exp
AppleUniversity of Central Missouri

Full-stack web developer with hands-on ownership of products from requirements through launch and maintenance, building across React and Node.js. Stands out for balancing product usability with technical performance, including API/database optimizations that improved performance by about 30% and shipping real-time dashboard features with scalable frontend/backend tradeoffs.

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CV

Principal Enterprise Architect specializing in product strategy and global platform modernization

Beverly Hills, CA12y exp
TicketmasterClaremont Graduate University

Engineering/technology leader from Ticketmaster who drove a domain-driven modernization strategy for legacy commerce platforms while launching new revenue features (add-on sales like merch/parking/hotels). Rebuilt and scaled teams post-COVID by reorganizing around business domains and implementing federated architecture governance, including a distributed-saga-based order orchestration approach that improved resilience and enabled partial-order success.

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PJ

Po Jui Lin

Screened

Mid-Level Full-Stack Engineer specializing in cloud platforms, cybersecurity web apps, and IoT

Seattle, WA3y exp
AmazonUniversity of Washington

Backend engineer with experience at Amazon building an API-driven service (APS) for large-scale prompt optimization jobs using AWS Step Functions, Batch/Fargate, DynamoDB, and S3, emphasizing idempotency, observability, and secure execution boundaries. Also led a multi-tenant enterprise policy/configuration backend refactor at MAMIT Cyber with versioned schemas, shadow writes, feature-flagged rollout, and PostgreSQL RLS-based tenant isolation.

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SS

Senior Salesforce Technical Lead specializing in enterprise CRM and integrations

Charlotte, NC13y exp
CenteneGautam Buddh Technical University

Salesforce-focused candidate with hands-on experience delivering Service Cloud automation, including entitlement/SLA escalation workflows, and building multi-component Lightning UI frameworks. Brings a mix of native-platform design, custom Apex extension, LWC architecture, and legacy Aura maintenance experience.

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YJ

Yili Jin

Screened

Intern Software Engineer specializing in data systems and machine learning

Remote, USA1y exp
TikTokPurdue University

Internship experience at TikTok and nCino, with hands-on work spanning production Python data pipelines, recommendation-system feature workflows, Salesforce Apex automation, and flaky UI automation for a live stock recommendation platform. Stands out for a reliability-focused approach: anticipating failure modes, instrumenting observability, and turning ambiguous business processes into maintainable automated systems.

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SB

Mid-level Full-Stack Developer specializing in cloud-native systems and AI/ML

6y exp
Capital OneUniversity of Texas at Dallas
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EZ

Senior Full-Stack Software Engineer specializing in scalable SaaS platforms

San Francisco, CA9y exp
AirtableUniversity of Texas at Dallas
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VB

Mid-level Full-Stack Developer specializing in FinTech SaaS

Remote, USA4y exp
PlaidUniversity of New Haven
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DS

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

TX, USA5y exp
AmazonCalifornia State University, East Bay
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Cheryl Qian - Junior Product Designer specializing in AI-powered SaaS products in New York, NY

Cheryl Qian

Screened

Junior Product Designer specializing in AI-powered SaaS products

New York, NY3y exp
Yacht LabsCornell University

Product-minded designer/builder who operates at the intersection of UX, support, and engineering. At Miter, they helped launch three products and built the customer-facing readiness layer that contributed to a 15% adoption increase; at Yacht Labs, they designed and implemented high-polish React/Next.js experiences and proposed a spec-driven app generation system to make AI output more controllable and trustworthy.

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HK

Mid-level Full-Stack Software Engineer specializing in cloud and data platforms

Boston, MA5y exp
Northeastern UniversityPenn State University

Full-stack engineer with experience spanning Amazon IMDb and Northeastern’s NeuroJSON portal, combining consumer product work with complex scientific data applications. Built IMDb’s streaming providers feature—described as the company’s most impactful feature of 2023—and has hands-on experience with React/Angular, GraphQL, AWS, Python services, and production monitoring.

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RV

Rucha Visal

Screened

Mid-Level Software Development Engineer specializing in distributed systems and full-stack web apps

Seattle, USA4y exp
AmazonUniversity of North Carolina at Charlotte

Software engineer who owned customer-facing, high-traffic TypeScript/React + TypeScript backend systems end-to-end, emphasizing safe velocity through feature flags, staged rollouts, observability, and rollback-ready incremental delivery. Reports shipping more frequently with fewer production incidents and faster recovery due to these guardrails.

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SR

Mid-Level Software Engineer specializing in AWS cloud services and microservices

Seattle, Washington4y exp
AmazonArizona State University

Software engineer with primary experience in Java and Python who also troubleshoots and optimizes JavaScript/React performance issues. Has handled customer-reported production problems via log-driven diagnosis and backend workflow fixes, and took ownership of simplifying and automating a service region-expansion process through time analysis and process documentation.

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SL

S Latha Naidu

Screened

Mid-level Software Development Engineer specializing in cloud-native backend systems

Seattle, WA5y exp
AmazonUniversity of Colorado Denver

Backend-focused engineer with experience at AWS building a global alarm processing platform (Python, Lambda/SQS/DynamoDB) handling traffic spikes and reliability issues; resolved duplicate alerts and latency under load by fixing hot partitions and enforcing idempotency. Previously at Cognizant, built Java/PostgreSQL backend workflows for healthcare dashboards using pre-aggregated summary tables, strong SQL optimization, and state-driven job orchestration with ELK-based observability and production guardrails.

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RC

Richard Cerow

Screened

Director of Marketing Technologies specializing in scalable web platforms for gaming

El Segundo, CA19y exp
KraftonUniversity of Notre Dame

Player-coach engineering leader focused on consumer-grade video/multimodal products and high-reliability identity/auth experiences. Led design and implementation of multi-step mobile login/MFA flows with telemetry-driven funnel improvements, shipped Node services and security fixes, and owned auth incidents end-to-end using RUM and step-level instrumentation. Introduced feature-flagged delivery and targeted review/testing practices to speed iteration ~20–30% while keeping login stability high.

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Manoj Manjunatha - Mid-Level Full-Stack Software Engineer specializing in cloud-native web platforms and AI tooling in Boise, ID

Mid-Level Full-Stack Software Engineer specializing in cloud-native web platforms and AI tooling

Boise, ID2y exp
Micron TechnologyUniversity of California

Built the backend for “codeGuard,” an AI-powered static code analysis platform, using FastAPI and Docker. Structured the system into API/service/execution layers and addressed heavy-workload container resource/cleanup issues via strict CPU/memory limits and a queued execution model.

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Harsh Sanas - Intern-level Software Engineer specializing in GenAI, RAG, and backend systems in San Francisco, CA

Harsh Sanas

Screened

Intern-level Software Engineer specializing in GenAI, RAG, and backend systems

San Francisco, CA2y exp
Scale AIUSC

AI/LLM engineer focused on shipping production-grade agents that automate support, sales intake, and ERP-connected workflows. Stands out for combining strong orchestration and guardrails with measurable business outcomes, including 45% faster support handling, ~$1.2M annual savings, 18% higher customer satisfaction, and 99.5%+ reliability in production.

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PK

Junior Software Engineer specializing in full-stack systems and distributed log analytics

Miami, FL1y exp
NeocisCarnegie Mellon University

CMU candidate with hands-on experience taking LLM concepts from research prototypes toward production-ready designs (structured outputs, guardrails, failure-scenario evaluation). Also partnered with sales/customer teams at Mazecare to drive adoption with Dontia Alliance (largest dental clinic chain in Singapore) and engaged Singapore government stakeholders, bridging clinical workflow needs with IT security/integration concerns.

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VS

Mid-Level Software Engineer specializing in full-stack web, AI telemetry, and real-time graphics

San Francisco, CA3y exp
C3 AINortheastern University

Product-focused full-stack engineer building a GenAI-powered case summarization workflow for a telemetry dashboard, spanning React/TypeScript UI (confidence indicators, reasoning traces) and Python/FastAPI backend with caching to control LLM latency/cost. Has operated services on AWS (ECS Fargate, RDS Postgres, S3) and Kubernetes, and has hands-on experience resolving real production latency incidents through query/index optimization and caching.

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VD

vikhyath D

Screened

Mid-Level Software Development Engineer specializing in distributed microservices on AWS

Dallas, TX5y exp
AmazonUniversity of North Texas

LLM/agent engineer who has shipped multiple autonomous, multi-step agents to production (document-to-SOP conversion, test generation, code generation) using a custom Python DAG orchestrator with persistent state, tool-calling permissions, and structured outputs (Pydantic/JSON Schema). Demonstrates strong production hardening practices—semantic contracts, golden-dataset prompt regression tests, circuit breakers, and multi-level monitoring—and delivered large productivity wins (34 hours of manual writing reduced to ~20 minutes review; ~15–20 engineering hours/week saved).

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