Vetted Mockito Professionals

Koushik Ravikumar

Screened

Mid-level Full-Stack Engineer specializing in cloud-native Java and AI platforms

Kyle, TX4y exp

“Full-stack engineer with strong cloud and platform experience spanning React, Go, AWS, Kafka, and Terraform. Has led complex migrations from monolithic/containerized systems to microservices and cloud deployments, built compliance-oriented logging infrastructure, and improved a broken frontend codebase to achieve a 3x performance gain while making it easier for other developers to extend.”

KAVYA UDATHA

Screened

Mid-level Full-Stack Java Developer specializing in retail, banking, and healthcare systems

Fairborn, OH5y exp

“Full-stack engineer with hands-on ownership of a real-time retail inventory and shipment tracking platform, spanning React/Angular dashboards through Spring Boot microservices, PostgreSQL, and Kafka. Stands out for building operationally impactful systems in ambiguous environments and for thinking carefully about scalability, monitoring, and user-friendly workflow automation, even without direct production AI experience.”

“Front-end/product engineer who has built an AI-assisted browser discussion platform combining vector-search-backed LLM responses with real-time chat, plus high-scale analytics interfaces for business users. Stands out for blending modern UI engineering with browser internals knowledge, including cross-browser extension behavior and tricky iOS Safari viewport/rendering issues.”

“Backend-leaning full-stack engineer who has shipped both a SaaS analytics/A-B testing platform and an AI-driven fraud monitoring product in production. Stands out for combining React/TypeScript frontend work with Python/Java backend systems, event-driven architecture, and practical LLM integration grounded by validation and human analyst feedback, with measurable impact on engagement, performance, fraud accuracy, and false positives.”

Yujun Liu

Screened

Junior AI software engineer specializing in agentic workflows and cloud platforms

Cambridge, MA3y exp

“AI/full-stack builder who has owned end-to-end LLM features in both creative tooling and education workflows. Built a multi-agent film-production workspace for Backlot and an automated ingestion pipeline at iOffer.AI that cut counselor manual entry by 70%, with hands-on depth in orchestration, validation, monitoring, and human-in-the-loop system design.”

Jaisurya Kolluru

Screened

Mid-level Software Engineer specializing in cloud-native backend and AI systems

Virginia, USA5y exp

“Full-stack engineer with hands-on ownership across React/TypeScript frontends, Node.js backends, and PostgreSQL on AWS. Stands out for production-focused database optimization, including execution-plan analysis, indexing, safe migrations, and architectural improvements that reduced database bottlenecks through a centralized REST API layer.”

“Backend-leaning engineer at Coforge with strong experience in subscription lifecycle and billing platforms, combining PostgreSQL, MongoDB, Azure, Kubernetes, and messaging systems. Stands out for owning production systems end to end and driving an event-driven architecture shift that reduced failures by 30%+ and improved response times by 40%.”

“Backend engineer with experience at KPMG evolving an audit/reporting platform from monolithic components to microservices (Spring Boot/Node.js), improving API performance and enabling independent deployments. Demonstrates strong production focus across secure API design (FastAPI, JWT/OAuth2, RBAC/RLS), incremental migrations with feature flags, and robustness improvements like optimistic locking to prevent race conditions.”

“Software engineer/product-focused builder who delivered real-time supply chain inventory dashboards to replace a legacy system, integrating directly with ERP/WMS/TMS to eliminate manual reporting. Uses TypeScript/React with Redux Toolkit on the frontend and microservices + REST APIs on the backend, with performance improvements via Redis caching and a strong focus on user-feedback-driven prioritization and observability in distributed systems.”

“Full-stack engineer who owned end-to-end delivery of a customer-facing financial services web platform and built internal tooling for engineering teams. Strong in microservices and event-driven systems (Kafka/RabbitMQ), distributed transaction management (saga), and production performance/observability—achieving ~40% backend response-time improvement through database and query optimization.”

“Full-stack engineer with enterprise experience at Metasystems Inc. (and Qualcomm) building high-traffic, security-sensitive systems—owned a secure transaction processing module end-to-end using Java/Spring Boot, Python/Django, and React. Strong AWS production operations (EKS/ECS/Lambda/RDS/DynamoDB) with IaC (Terraform/CloudFormation), observability, and reliability patterns; also delivered resilient ETL/integration pipelines with idempotency/retries/backfills and achieved a 50% deployment-time reduction through CI/CD and modular refactoring.”

“Backend engineer with experience building Spring Boot microservices for financial workflows at Fizzle (thousands of requests/minute) and shipping healthcare data validation automation at CVS Health. Demonstrates strong production reliability/performance skills—deep in database tuning (query plans, indexing, caching, denormalization), observability (Prometheus/Grafana), and resilient multi-step workflow design with retries and human-in-the-loop escalation.”

“Full-stack engineer with experience at Capital One and Prime Softech owning production systems end-to-end: secure authentication (Java/Spring Security + React/Redux) through AWS ECS deployments with Terraform and CI/CD. Strong reliability/observability focus (Prometheus/Grafana/ELK/CloudWatch) with quantified improvements (15% reliability gain, 30% fewer post-release defects). Also led legacy monolith-to-microservices refactors and built real-time Kafka/Spark ingestion pipelines for analytics/fraud detection.”

“Full-stack engineer experienced shipping production SaaS dashboards with Next.js App Router + TypeScript, combining Server Components for initial data loads with interactive client-side analytics. Strong performance/operability focus (reported ~40% UI latency reduction) and deep backend fundamentals across Postgres schema/query optimization and Kafka-based event-driven microservices with idempotency, retries, and DLQs.”

“Built and deployed a live production LLM document Q&A platform (DocumindAI) with an adaptive RAG pipeline (Claude + Cohere embeddings + pgvector), source-cited structured outputs, and engineered fallbacks for reliability and sub-2s latency. Also has enterprise integration experience at Tech Mahindra working with messy IFS ERP XML integrations, using validation/normalization and JTA transactions to prevent partial writes and data corruption.”

“Accenture consultant who shipped an LLM-based production solution during a client cloud migration to parse application code and identify only the database objects actually used, cutting migration time by 30% and accelerating realization of cloud cost benefits. Emphasizes production robustness with timeouts/retries/fallback routing, validation, observability, and a disciplined eval/monitoring loop that turns failures into regression tests.”

Sharanya Teegala

Screened

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

Minneapolis, MN5y exp

“Full-stack engineer with experience at Wells Fargo and Salesforce building regulated, customer-facing financial systems and internal DevOps tooling. Deep in microservices and event-driven architectures (Spring Boot, Kafka/RabbitMQ) with strong CI/CD automation, contract testing, and observability; delivered measurable impact including 60% faster deployments and 40% fewer support tickets.”

Bandla Sai Giridhar

Screened

Mid-level Software Engineer specializing in full-stack and cloud-native microservices

Dallas, TX4y exp

“Backend engineer who built a Python/Flask system for high-volume healthcare claims processing, using PostgreSQL as the source of truth and RabbitMQ workers for scalable async processing. Experienced in SQLAlchemy/Postgres performance tuning, multi-tenant data isolation (including Postgres RLS), and integrating/versioning ML model services (scikit-learn/PyTorch/Hugging Face) with controlled rollouts. Drove measurable performance gains by batching background jobs and adding Redis caching (40% less workload; response times cut from ~10s to 2–3s).”

William Goff

Screened

Principal Software Engineer specializing in MongoDB and Java platforms

San Mateo, CA10y exp

“Government and defense software architect with a track record of building mission-critical systems from prototype to long-lived production. Most notably designed Banyan at Fort Meade, a federated SOA platform that achieved 99.9999 uptime and handled 3.2 million daily queries, and later built SBOM automation at Lockheed Martin that was contributed back to the CycloneDX open source ecosystem.”

Lawrence Prabhakar

Screened

Mid-level Full-Stack Java Developer specializing in FinTech

USA5y exp

“Engineer with a thoughtful, hands-on approach to AI-assisted software development, treating AI as a force multiplier for debugging, prototyping, and large-codebase work rather than a substitute for judgment. Particularly strong in multi-agent coding workflows, contract-driven development, and maintaining consistency across backend, frontend, and testing through shared schemas and OpenAPI-based coordination.”

Aniket Dhanawade

Screened

Mid-level Full-Stack Engineer specializing in cloud-native and AI-powered applications

USA3y exp

“Candidate has a thoughtful, hands-on approach to AI-assisted software development, treating AI as a pair programmer while retaining ownership of architecture, tradeoffs, and final code quality. They have practical experience using multi-agent workflows to ship small features end-to-end, including planning, execution, and gap detection under human oversight.”

“Backend engineer who shipped a Spring Boot transactions/points feature while using AI selectively for boilerplate and test ideas, keeping core system design decisions in human hands. Stands out for rigorous validation of AI output against database behavior, concurrency, idempotency, and failure scenarios, and has also built a lightweight planner -> code gen -> validator agent-style pipeline with step-level logging and retries.”

“Full-stack engineer with experience spanning AI-powered product features and healthcare fraud detection systems. Has built end-to-end LLM-enabled applications, customer-facing recommendation systems at scale, and operational platforms that improved real-time investigations and flagged over 1,200 high-risk cases quarterly.”