Vetted Jenkins Professionals

“JavaScript/React performance-focused engineer who contributed upstream to an open-source virtualization/pagination library, fixing overlapping-fetch race conditions and introducing prefetch/deduping patterns that cut load times from ~3s to <900ms and reduced render thrash ~35%. Also built healthcare automation systems (clinical summary and claims triage), including a FastAPI + RAG pipeline that retrieved CPT/ICD evidence, improving decision accuracy from 67% to 86% and reducing turnaround time by 40%.”

“Backend engineer who built and optimized a high-traffic e-commerce platform in Python/Flask, focusing on scalability and reliability through service decomposition, Redis caching, and Celery-based background processing. Also integrated an AI intent-classification chatbot as a separately deployable inference service on AWS and has hands-on experience designing multi-tenant data isolation strategies in PostgreSQL.”

“Full-stack engineer who owned enterprise workflow platforms end-to-end at Northern Trust and Elevance Health—building NestJS/Java Spring Boot APIs, React UIs, and cloud deployments on GCP Cloud Run. Strong in data-heavy applications (hundreds of thousands of records) with proven production performance tuning (indexing/query rewrites, Cloud Run concurrency/min instances) and secure RBAC via Azure AD.”

“Software engineer with experience delivering customer-facing and internal tools across GE Renewables, GE Healthcare (supply chain/production systems), and a Boulder-based event app startup. Recently focused on scaling backend performance using Redis and RabbitMQ, and has hands-on experience resolving hard-to-reproduce production issues in legacy authentication/session systems; also deployed a personal project (Journal Buddy) publicly.”

“Backend engineer with hands-on ownership of FastAPI/Django services using MongoDB and React integration, focused on production reliability and performance (Redis caching, Celery background jobs, automated testing). Has delivered AWS container deployments via GitHub Actions to ECR with scripted rollouts/health checks, and supported phased migrations with replication and rollback planning. Also built a real-time user-activity streaming pipeline addressing partition hot spots and consumer lag through partition-key strategy, idempotency, and monitoring.”

“Built and productionized an agentic LLM workflow during a summer internship to transform unstructured clinical reports into analytics-ready structured data, using a LangChain multi-agent design plus an LLM-as-a-judge layer to control quality in a regulated setting. Also has experience orchestrating ML pipelines at Piramal Capital using AWS Step Functions/EventBridge/CloudWatch, with strong emphasis on observability, evaluation rigor, and measurable impact (80–90% reduction in manual data entry).”

“Backend-leaning full-stack engineer who ships AI-enabled products end-to-end: built CodeChat, a production internal codebase Q&A tool using RAG with Pinecone and a model-agnostic wrapper across OpenAI/Anthropic/AWS Bedrock, cutting AWS costs ~50% and latency ~45%. Also built and operated RealityStream, a Flask-based real-time forecasting API with JWT/RBAC, MLflow model versioning, and Prometheus/Grafana observability, including handling a real production latency incident via rollback, preloading, and caching.”

“ML/NLP engineer with experience at Charles Schwab building an NLP + graph (Neo4j) entity-resolution system to unify fragmented user/device/transaction data and improve downstream model quality and analyst querying. Has applied embeddings (SentenceTransformers + FAISS) with domain fine-tuning to boost hard-case matching recall by ~12% while maintaining precision, and has a track record of hardening scalable Python/Spark pipelines and productionizing fraud models via A/B tests and shadow-mode monitoring.”

“QA automation engineer who owned an end-to-end automated regression suite for a PlayStation digital store flow (login through checkout/payment), building a hybrid POM/data-driven framework from scratch with Selenium/TestNG/Cucumber and also using Playwright/TypeScript and Cypress. Integrated the suite into Jenkins CI/CD with nightly runs and reporting, improved coverage (happy + negative paths), and reduced release risk by catching critical issues like session timeout and transaction/payment defects before production.”

“IBM Power/AIX infrastructure engineer who has owned a large AIX 7.x/VIOS/HMC estate (hundreds of LPARs), handling provisioning, patching, tuning, and incident response. Demonstrated high-availability and recovery leadership with PowerHA failovers and SAN-path RCA/resiliency improvements, plus successful AIX 7.1→7.3 migrations with minimal downtime/no data loss. Also brings modern DevOps/IaC experience (Jenkins + Vault, Docker/Kubernetes, Terraform on Azure) with a focus on secure, repeatable deployments and drift control.”

“Built an end-to-end automated trading system for Polymarket, including Go/Python execution services, Terraform-scheduled ETL/feature pipelines, and monitoring on modest hardware. Also shipped a production LLM+RAG signal verifier/explainer that grounds trade decisions in external context (news/social) with vector DB retrieval and guardrails, plus a lightweight RAGAS-style eval loop on ~50 resolved markets that improved signal faithfulness by ~15%.”

“Early engineer at a fast-growing startup who owned an AI-powered portfolio/site generation workflow end-to-end (frontend in Next.js App Router/TypeScript through backend orchestration). Emphasizes server-first security/performance (Server Components/Actions, revalidation), and production hardening with validation, caching, observability, retries/idempotency, and CI/E2E testing.”

“Built and shipped production RAG-based LLM agents automating multi-step document query workflows, emphasizing reliability via monitoring, retries, structured exception handling, and fallback retrieval (alternative embeddings/keyword search). Demonstrated measurable gains (18% latency improvement, 25% retrieval efficiency, 12% precision) and has experience integrating agents with messy tax and transaction data at RSM using validation/cleaning and idempotent design.”

Subhash Krishnamoorthy

Screened

Executive Technology Leader specializing in digital transformation, headless e-commerce, and cloud architecture

Chesterfield, VA25y exp

“Technology leader focused on business-aligned roadmaps and integration-heavy ecommerce platforms. Recently delivered an on-time launch for lutusooking.com (a premium Hamilton Beach brand) by coordinating UX/UI, component-based middleware, BigCommerce, Algolia search, personalization/recommendations, payments, and supply chain integrations, and later improved scalability via a Jitterbit iPaaS approach proven during Black Friday/Cyber Monday traffic.”

“Full-stack engineer who built an AI-driven document analysis and processing workflow end-to-end, including large-document ingestion, queued async processing, and low-latency retrieval for user-facing flows. Demonstrated practical performance tuning (moving heavy work off request path, polling, caching) and Postgres optimization validated with EXPLAIN ANALYZE, plus durable workflow resilience via retries and dead-letter queues.”

“Data engineer focused on AWS + Spark/Databricks pipelines, including an end-to-end nightly loan-data ingestion flow (~2.2M records) from Postgres/S3 through Glue and Databricks into a DWH with layered validation and alerting. Also built real-time streaming with Kafka + Spark Structured Streaming and a master’s project streaming Reddit data for sentiment analysis under ambiguous requirements and tight budget constraints.”

Muaaz Syed

Screened

Mid-level AI/ML Engineer specializing in NLP and conversational AI

Richardson, TX4y exp

“ML/NLP engineer focused on real-time IT ops analytics, building a predictive maintenance/anomaly detection platform end-to-end (multi-source ETL, streaming, modeling, and production deployment on GCP/Vertex AI). Uses deep learning (LSTMs, autoencoders/VAEs) plus embeddings (SentenceBERT) and vector search to improve incident correlation and search, citing ~40% reduction in duplicate alert noise.”

Ramcharan Reddy

Screened

Mid-level Full-Stack Developer specializing in FinTech platforms and cloud-native microservices

Texas, USA6y exp

“Backend engineer focused on AI-enabled systems, having built a production-style RAG pipeline (vector search + LLM) exposed via Python/Flask endpoints with strong observability and hallucination-reduction techniques. Demonstrates deep performance work in PostgreSQL/SQLAlchemy (5x faster analytics queries) and high-throughput optimization using Celery + Redis (800ms to 120ms latency, 3x throughput), plus schema-per-tenant multi-tenancy with tenant-aware middleware and logging.”

Sreeja Venkatakrishnan

Screened

Mid-level Full-Stack Developer specializing in Java/Spring and modern JavaScript frameworks

Virginia, USA4y exp

“Full-stack engineer with hands-on experience building real-time applications (Socket.io chat app) and data-heavy systems in banking/loan management. Comfortable across React and backend services (Spring Boot/Node), with a focus on scalable API design, database performance (indexing/pagination/caching), and deployment via CI/CD and cloud infrastructure.”

Siddhartha Alapati

Screened

Mid-Level Software Engineer specializing in Java/Spring microservices and full-stack web apps

Denton, TX4y exp

“Software/full-stack engineer focused on deploying and integrating microservice applications into production AWS and hybrid cloud/on-prem industrial environments. Demonstrated end-to-end troubleshooting by tracing intermittent user failures to network routing/packet loss caused by load balancer and NIC misconfiguration, then adding monitoring to prevent recurrence. Also delivers customer-specific Python extensions with strong validation, testing, and backward compatibility.”

Shivani Sharma

Screened

Mid-Level Software Engineer specializing in Cloud, DevOps, and MLOps

Boston, MA3y exp

“Built and productionized a recommendation system from notebook prototype into a low-latency, scalable Cloud Run service using Docker, FastAPI, Terraform, CI/CD (GitHub Actions), and MLOps tooling (Vertex AI, MLflow). Experienced diagnosing real-time workflow issues using structured logging/ELK and GCP metrics, including resolving intermittent 504s by fixing unbounded SQL and adding caching. Also partners with sales/customer teams (Wasabi) to deliver tailored demos, troubleshoot, and drive onboarding/adoption.”

Sowbhagya Vegunta

Screened

Senior Front-End Developer specializing in React, Angular, and accessible UI

GTA, ON8y exp

“Frontend engineer who led end-to-end delivery of a complex, real-time dashboard/discovery and admin workflow module using React + TypeScript + Redux. Emphasizes quality at scale through automated testing (Jest/Playwright), accessibility validation (NVDA/axe), and reusable component architecture (Storybook), and has hands-on experience solving performance issues via bundle analysis and route-based lazy loading/code splitting.”

Naga Chandra mouli Thammineni

Screened

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

Hyderabad, Telangana, India2y exp

“Software engineer who built and owned a centralized Asset Management platform at Hyundai Mobis used daily by multiple internal teams, delivering everything from UI/TypeScript React frontend to Spring Boot services, databases, deployment, and post-release support. Experienced in scaling microservices with Kafka-based async workflows, improving data consistency/real-time updates, and implementing reliability patterns like standardized API contracts, retries, DLQs, and targeted caching.”