Vetted Redux Toolkit Professionals

“Open-source contributor who improved React Query’s caching/subscription behavior to reduce unnecessary re-renders via debouncing and batched updates, validated with benchmarking and extensive tests. Also maintained a Flask extension and resolved production background-task hangs by tracing Redis connection handling issues, adding cleanup/retry logic and troubleshooting docs. In a fast-paced startup, owned the design of a Celery+Redis multi-queue background processing system with Prometheus-based observability.”

Sri Lalitha

Screened

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

California, USA6y exp

“Backend engineer who owned a Python task management API with JWT auth, async notifications, and performance work (DB optimization/caching) to handle high volumes. Led an on-prem to Azure private cloud migration at Morgan Stanley using GitOps and IaC (Terraform/ARM) with phased rollout and rollback planning. Also built a Kafka real-time streaming pipeline with exactly-once/idempotent consumers and Prometheus/Grafana monitoring.”

Ashwitha Reddy

Screened

Mid-level Full-Stack Software Engineer specializing in Java/Spring microservices and AWS

Ohio, United States3y exp

“Backend/platform engineer who has owned a real-time business analytics dashboard backend (Python/Flask/MongoDB) and built Kafka event-streaming pipelines with idempotent processing and DLQs. Strong DevOps/GitOps experience deploying containerized microservices to AWS EKS with CI/CD (Jenkins/GitHub Actions/CodePipeline) and ArgoCD auto-sync/drift detection, plus hands-on support for phased hybrid cloud/on-prem migrations using feature flags and replication.”

Jake Lee

Screened

Junior Full-Stack/Systems Engineer specializing in AI, embedded systems, and healthcare apps

Boston, MA3y exp

“Led architecture for “Solstice/Solstis,” a safety-aware, hands-free AI medical assistant that guides users through minor emergencies with a structured, state-machine-driven LLM agent integrated with device hardware. Built RAG grounded in Red Cross procedures plus guardrails, fallbacks, and emergency escalation, and improved real-world usability by shifting from open-ended chat to a deterministic step-by-step workflow measured via completion rate, repeat prompts, and latency.”

“Backend engineer with hands-on ownership of banking microservices from initial design to launch and production support, including security, CI/CD, observability, and incident response. Stands out for measurable modernization impact—~35% faster backend processing, ~40% lower query latency, and ~30% better deployment cycles—and for a pragmatic approach to both Kafka-based async systems and controlled LLM integration in enterprise workflows.”

“Full-stack/product-minded engineer with strong React/TypeScript depth who has owned systems end-to-end, from UI architecture to backend services and data design. At Qualcomm, they built both a telemetry dashboard and an ML model drift monitoring platform for 20+ edge models, including post-launch tuning that cut false positives by 60%. They also demonstrate 0→1 startup execution by solo-building a production RAG document Q&A platform with JWT auth, Stripe gating, and sub-300ms retrieval.”

“Engineer working on high-throughput financial systems who uses AI pragmatically to accelerate development without sacrificing design ownership, correctness, or compliance. Particularly interesting for teams building regulated, real-time platforms: they have hands-on experience integrating fraud detection models into microservices, handling transaction ingestion, scoring, decisioning, and throughput-sensitive asynchronous workflows.”

Prashant Salunke

Screened

Mid-Level Software Development Engineer specializing in full-stack and cloud-native systems

Chicago, IL4y exp

“Backend engineer who has shipped production LLM-powered features, including an AI-assisted developer tool on AWS (Spring Boot) and a blog platform capability using embeddings + Elasticsearch for semantic retrieval and LLM-generated summaries/recommendations. Demonstrates practical tradeoff management (quality/latency/cost), guardrails to reduce hallucinations, and evaluation-driven iteration using real user queries and observability via ELK.”

Deeresh Gajjala

Screened

Senior Software Engineer specializing in Java/Spring Boot microservices and AWS payments systems

Dallas, TX6y exp

“Senior software engineer with Amazon experience who owned end-to-end improvements to a real-time payment authorization service, rebuilding it as a reactive Spring WebFlux microservice with saga orchestration and Kafka event streaming, deployed on AWS EKS with strong observability. Also built React+TypeScript and Node/Express full-stack workflow apps (onboarding, campaign management, admin review) and has experience shipping quickly in ambiguous startup environments while maintaining reliability and data correctness.”

Ajay Desai

Screened

Mid-level Full-Stack Software Engineer specializing in FinTech and backend platforms

USA4y exp

“Built an AI-native legal research platform that automated analysis across 100,000+ dense legal documents, combining LLM workflows, async backend architecture, and conversational retrieval in production. Also brings cross-domain experience in investment-analysis agents and healthcare claims/billing systems, with a strong emphasis on reliability, deterministic orchestration, and safe handling of messy operational data.”

“Frontend-focused engineer at YTech Global with roughly 3.5 years on a logistics contract management platform, owning major pieces of architecture for micro frontends, real-time workflows, and operational dashboards. They describe building the first UI-based contract management experience for shippers and carriers, helping grow usage from 10,000 to 20,000 users while partnering closely with backend teams on API and WebSocket design.”

Sanket Mungikar

Screened

Mid-level Software Engineer specializing in distributed backend and AI analytics platforms

California, USA4y exp

“Full-stack engineer at BigCommerce who combines customer-facing deployment ownership with hands-on AI/LLM systems work. Built and launched merchant analytics and predictive inventory workflows using React, TypeScript, FastAPI, Kafka, AWS, and RAG-style architectures, and has real production experience debugging non-deterministic AI issues caused by data pipeline freshness and event-ordering problems.”

Sai Divya Mulukala

Screened

Mid-level Full-Stack Software Engineer specializing in FinTech and distributed systems

USA5y exp

“Full-stack engineer with experience building operational dashboards at Walmart and improving digital banking experiences at Bank of America. Stands out for tracing performance issues across frontend, APIs, and backend services, including cutting response times from 1.2s to 700ms and resolving duplicate event-processing problems in distributed systems.”

“Full-stack engineer specializing in Java Spring Boot microservices and React, with hands-on ownership of a merchant dispute management platform (security via RBAC/JWT, significant performance gains through SQL execution-plan-driven tuning and UI refactors). Also has experience at JPMorgan Chase optimizing high-volume financial-data services with API efficiency, caching, and async processing.”

Kiran M

Screened

Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices and data platforms

Bentonville, AR5y exp

“Backend/ML integration engineer with experience at Accenture and Walmart building Flask-based analytics and prediction APIs on PostgreSQL/MySQL. Strong focus on performance and scalability—uses precomputed aggregates, Redis caching, query tuning (indexes/partitioning/EXPLAIN), and async/background processing; also designs secure multi-tenant isolation with JWT and schema/db-per-tenant strategies.”

Pravalika Kasojjala

Screened

Mid-level AI/ML Engineer specializing in LLM, RAG/GraphRAG, and fraud analytics

Charlotte, NC5y exp

“LLM/agent engineer who has deployed a production internal assistant to reduce employee inquiry resolution time while maintaining regulatory compliance. Experienced with RAG, hallucination risk triage, and graph-based orchestration (LangGraph) for enterprise/banking-style workflows, emphasizing schema-validated, citation-backed, tool-constrained agent designs and tight collaboration with non-technical business/compliance stakeholders.”

Michael Yeung

Screened

Mid-level Software Engineer specializing in FinTech trading platforms

San Francisco, CA4y exp

“Built and deployed internal trading tools at Wells Fargo that reduced manual production-support dependency for trader configuration workflows. Brings hands-on experience in financial systems, data quality, and production incident resolution, including building 400+ SQL validation rules and designing an internal RAG assistant for engineering documentation.”

“Entry-level backend engineer currently building AI infrastructure for a legal-tech product, including message APIs between frontend and LLMs and MCP-based integrations to enterprise legal systems. Stands out for owning backend components end-to-end in an ambiguous early-stage environment and for resolving a critical pre-demo bug under intense time pressure.”