Vetted Stored Procedures Professionals

“Customer-facing software engineer who rapidly turns business requirements into Figma prototypes and PoC applications, using workflow prioritization and frequent client reviews to stay aligned. Has hands-on experience integrating with existing authentication/user APIs, building MongoDB-backed caching, and implementing robust fallback/retry mechanisms. Comfortable working on-site with customers and resolving production issues in AWS (e.g., DNS/EC2 traffic routing) in collaboration with DevOps.”

“Robotics-focused full-stack engineer with hands-on ROS experience building sensor-processing and control nodes, plus a track record of debugging and optimizing real-time robot responsiveness via profiling and message-timing analysis. Uses Webots for pre-hardware validation and Docker/CI/CD to standardize deployments and catch issues early.”

“Gameplay engineer with hands-on ownership of real-time C++/UE5 systems, including an end-to-end ability system and a networked dash feature using client prediction and server reconciliation. Strong in performance profiling/optimization (object pooling, collision-check gating) and applied math for projectile motion validated via debug visualization and QA/playtesting; particularly interested in soccer/football gameplay mechanics and feel.”

“LLM/agentic-systems practitioner who has repeatedly taken LLM-driven pricing/decision services from prototype to production using pilots, guardrails, observability, and staged rollouts. Demonstrates strong real-time incident troubleshooting (dependency timeouts, cached fallbacks) and post-incident hardening (isolation/async/alerts), and also supports go-to-market via developer workshops, technical demos, and sales-aligned POCs.”

“Built and operated an end-to-end customer-facing "Record Platform" web product as both engineer and primary user, focusing on reliability and correctness in core flows like search and checkout. Implemented a TypeScript/React frontend with a multi-service backend and Kafka-based event-driven architecture, and created internal tooling to automate risky ops like Kubernetes TLS certificate rotation with k6 load/chaos testing (including HTTP/2 and HTTP/3 validation).”

“Frontend-focused engineer with enterprise Angular experience integrated with .NET APIs, emphasizing production-ready practices (reusable components, modular architecture, TypeScript standards, Jasmine unit tests, and CI/CD). Has not built Unreal Engine UI systems yet, but articulates how they would translate web UI modularity, separation of concerns, and testing/automation practices to Unreal/CommonUI workflows.”

Manasa Pippera

Screened

Senior .NET Full-Stack Developer specializing in cloud, IoT messaging, and real-time web apps

Franklin, TN6y exp

“Full-stack engineer who owns customer-facing web products end-to-end (React/TypeScript + Node.js), shipping frequent releases with strong testing, staged deploys, and production monitoring. Improved a key user flow by batching backend calls and simplifying frontend rendering, driving ~30% faster load times and ~30% higher completion rates. Also built an ops monitoring dashboard using ELK + Prometheus/Grafana that cut incident response time by 40% and has hands-on microservices messaging experience (RabbitMQ/Kafka, idempotency, DLQs).”

Rambabu Dhanavath

Screened

Mid-level Software Engineer specializing in backend and cloud-native microservices

United States5y exp

“Backend/cloud engineer with 5 years of experience who has shipped a production internal ops LLM assistant end-to-end using Spring Boot microservices on AWS. Stands out for designing controlled, safety-first agent orchestration with deterministic tool access, Redis/DB-backed recoverable state, and strong observability/evaluation practices to improve reliability in production.”

Nidhip Patel

Screened

Mid-level Software Engineer specializing in AI/ML and full-stack systems

United States3y exp

“Backend Java engineer with strong platform/DevOps experience: modernized an insurance claims legacy monolith into DDD-aligned microservices, deployed containerized services on Kubernetes with Jenkins CI/CD and static analysis gates, and implemented GitOps using ArgoCD. Also led major AWS migration planning with dependency mapping and network monitoring to uncover hidden dependencies, and built Kafka-based real-time event streaming with schema-registry-driven evolution.”

“Built and owned UPS tracking/reporting and operations workflow dashboards, delivering customer-facing APIs and real-time React/TypeScript UIs backed by .NET Core. Experienced in high-volume microservices using IBM MQ/Azure Service Bus with strong reliability patterns (idempotency, retries, DLQ) and Azure-based observability, plus performance tuning across frontend and SQL-backed services.”

“Full-stack engineer with strong React/TypeScript and Java Spring Boot microservices experience who has built end-to-end task management and real-time, data-intensive dashboards. Demonstrates practical depth in security (JWT, RBAC, token refresh), performance optimization (indexing/aggregations, virtualization, caching), and cloud deployment (AWS, Docker, Jenkins, Kubernetes).”

“Product-focused full-stack engineer (Spring Boot/Django + React/TypeScript) with deep experience building multi-tenant, enterprise workflow and supply-chain/order-tracking systems. Owned an end-to-end Workflow SLA Breach Prediction & Alerting feature integrating Azure ML for a cloud workflow platform used by ~10,000 enterprise users, and has hands-on AWS operations experience resolving real production latency/scaling incidents via query optimization and Redis caching.”

“Software engineer who built and open-sourced reusable React/Node.js modules (chat, auth, caching) from an AI education platform, emphasizing intuitive APIs and strong documentation. At TCS, improved a healthcare scheduling platform by diagnosing SQL/server bottlenecks and redesigning database + caching, cutting appointment load times by ~40% and reducing support complaints.”

“Software engineer with experience at Wipro Technologies and Wells Fargo building React-based SPAs, reusable component libraries, and developer documentation. Demonstrated strong performance engineering (React.memo, list virtualization, code splitting) with reported >50% rendering-time improvement, plus hands-on production support by diagnosing API outages via monitoring/logs and implementing traffic/server fixes. Comfortable leading workstreams in fast-changing environments using Kanban and tight stakeholder feedback loops.”

“Backend-leaning full-stack engineer who led a legacy monolith-to-microservices migration (OAuth, Redis, ActiveMQ) while shipping incrementally via CI/CD to avoid user disruption. Strong in search/filter experiences and performance tuning (Solr schema + relevance boosting) with measurable impact (login reduced to ~5s), plus React/TypeScript UI work including configuration-driven filters and shareable URL state.”

Navya Sureddy

Screened

Mid-level Full-Stack Developer specializing in Angular/React and Spring Boot

Columbus, IN5y exp

“Full-stack engineer with experience at Cummins owning production features end-to-end (React/TypeScript + Node + Postgres) and operating them in AWS (EC2/RDS/S3/IAM) with CloudWatch-based observability. Also built resilient ETL and third-party integrations, including an AWS Glue–S3–Redshift pipeline hardened with validation, idempotent UPSERTs, retries/backfills, and quarantine handling to prevent bad or duplicate data.”

Varun Kothapalli

Screened

Mid-level AI/Machine Learning Engineer specializing in Generative AI, NLP, and MLOps

Saint Louis, MO6y exp

“Built a production LLM/RAG document analysis system for large financial documents (credit reports/PDFs) to help business analysts extract insights faster. Implemented end-to-end pipeline orchestration with LangChain, vector search (e.g., FAISS), and hallucination controls (context grounding, similarity thresholds, and no-answer fallback), delivered as a Dockerized Python API.”

“Backend engineer with hands-on experience scaling a CVE processing platform by re-architecting it into a Kafka-based distributed system, boosting throughput to 200k+ records/min while designing for HA, deduplication, and fault tolerance. Also led a Flyway-driven migration affecting 15M+ records with staged dev→stage→prod rollout, and has implemented production security patterns (Auth0, OAuth2/HTTPS, AWS IAM RBAC) including least-privilege hardening.”

“Full-stack engineer who has owned React/TypeScript + Spring Boot dashboard products end-to-end, including real-time performance/alerts and data aggregation across services. Strong in shipping MVPs quickly with feature flags, automated testing and CI/CD, and using monitoring/click-path analytics to prioritize work—achieved a 40% page-load reduction. Experienced operating microservices with RabbitMQ at scale, addressing retries/idempotency/observability and fixing duplicate-processing incidents with idempotent consumer patterns and DLQs.”

“Data engineer with banking FP&A experience who led an end-to-end migration of 10+ TB from Teradata to Azure (ADF + Data Lake + Databricks/PySpark + Synapse). Emphasizes reliability (multi-stage validation, monitoring/alerts) and performance (Spark tuning, incremental loads, autoscaling), reporting ~99.5% pipeline reliability while supporting downstream consumers with stable schemas and clear change management.”

“Data/analytics engineer focused on finance and e-commerce integrations, building end-to-end pipelines and services across Odoo, QuickBooks, Snowflake, and Tableau. Replaced a costly third-party Walmart connector with a serverless AWS Lambda pipeline deployed via Terraform/GitHub and monitored with CloudWatch/Datadog, and shipped a bi-directional Odoo↔QuickBooks invoice sync with distributed locking plus Slack-based finance approvals.”

Almas Fathimah

Screened

Senior AI Engineer specializing in Generative AI and ML platforms

USA7y exp

“Built and owned a production RAG-based conversational AI system at Entera for real estate analysis, taking it from experimentation through AWS deployment, monitoring, and iterative improvement. Demonstrates strong practical judgment in retrieval design, LLM safety, and scalable Python service architecture, with measurable impact including 30-40% reduction in manual analysis time and roughly 30% better response accuracy.”

“Built a production AI stylist agent for retail store associates that pulls customer loyalty, address, and purchase-history data to generate in-store product recommendations. Demonstrates hands-on experience across agent orchestration, MCP-based tool integration, Vertex AI/GCP deployment, observability, resilience patterns, and pragmatic production tradeoffs like using PostgreSQL with pgvector instead of a standalone vector database.”