Vetted CI/CD Professionals

“Frontend engineer who led a networking-device simulation PoC into a production-integrated product, designing microservice-style containerized architecture and optimizing massive telemetry streams with WebSockets and Kubernetes-based scaling. Built a React+TypeScript network orchestration dashboard (Platina Command Center) and drove quality/performance through unit/E2E testing with measurable browser/API performance metrics and CI/CD automation for rapid monthly releases.”

“Frontend engineer focused on scalable architecture and long-term maintainability, emphasizing modular component design in React + TypeScript. Has experience building reusable component libraries (including Storybook and shared repos) and collaborating with design/product to refine UX workflows, reducing development time over successive iterations.”

“Data engineer in financial services (Northern Trust) who has worked across ingestion, transformation, data quality, orchestration, and serving on AWS (S3/Glue/EMR) with Airflow. Highlights include processing ~15M transactions with validation/anomaly detection for regulatory reporting and improving Snowflake query performance by 27% for risk/compliance reporting. Also built a personal real-time streaming service (FastAPI, Kafka, Redis, Cassandra) and uses production reliability patterns like blue-green/atomic swaps and robust retry strategies.”

Punith Jayaramu

Screened

Mid-Level Full-Stack Software Engineer specializing in FinTech and Mortgage systems

Auburn Hills, MI3y exp

“Full-stack engineer with deep AWS serverless and reliability experience in fintech/underwriting systems, including eligibility scoring and dynamic rule deployments. Built and productionized an LLM-powered incident RCA assistant (Bedrock Claude 3 + custom RAG + React) achieving 92% precision and ~75% MTTR reduction, with mature guardrails (evals, drift monitoring, HITL, audit logs) and strong operational rigor (canaries, chaos testing, DLQ remediation).”

Nazar Fedyk

Screened

Senior QA Automation Engineer specializing in end-to-end and API test automation

Chicago, IL7y exp

“QA automation engineer in a banking domain who owned an end-to-end automation suite for critical money movement flows (onboarding, funding, transfers). Demonstrated impact through edge-case coverage (min balance, boundary amounts, repeated actions, timeouts), CI/CD gating with smoke vs regression suites, and catching a high-impact timing defect where UI success masked incorrect balance updates.”

Sridhar Duggireddy

Screened

Executive Technology Leader specializing in Cloud Platforms, DevOps, and AI/ML

Tampa, FL21y exp

“Early-stage startup CTO helping build an AI-powered parenting assistant app with features spanning advice, shopping, task management, and inventory management. The team is currently testing an MVP with their network while the candidate simultaneously learns the seed/Series fundraising process through Connectd and early investor conversations.”

Dhananjay Dubey

Screened

Senior Full-Stack Game Engineer specializing in multiplayer Unity and mobile systems

Newark, NJ6y exp

“Unity/C# game developer with hands-on experience shipping large-scale multiplayer mobile games, including titles cited at 1M+ and 10M+ downloads. Combines real-time networking and physics optimization expertise with AI/MR research experience, including an IEEE-published sports coaching system using pose estimation, SMPL-X, and LSTM models. Particularly strong in latency-sensitive, cross-platform interactive systems spanning mobile, multiplayer, and mixed reality.”

Rangel Koli

Screened

Entry-level Software Engineer specializing in backend and cloud systems

New York City, NY1y exp

“Backend engineer who built and scaled a zero-to-one social product backend using Supabase (Postgres, Edge Functions, Auth, Realtime) plus Neo4j for graph-based friend recommendations. Demonstrates strong production rigor: staged rollouts with metrics, incident rollback/postmortems, and complex schema refactors using expand-contract/dual-write with reconciliation and feature flags. Notably proactive about edge cases like geo-boundary realtime delivery and idempotent retry safety.”

“AI-focused engineer with Infosys experience building Azure/.NET chatbot applications and recent hands-on work with FastAPI/LangChain. Built a hackathon multi-agent legal counsel system showcasing agent orchestration, and emphasizes production readiness via Docker, GitHub Actions CI/CD, pytest automation, and adversarial simulations for auditable AI behavior. No direct robotics/ROS experience to date.”

“Frontend engineer (Teradata) who led an enterprise analytics dashboard end-to-end, building complex React + TypeScript interfaces with near-real-time updates and large data volumes. Strong track record in scalable frontend architecture, performance tuning (render optimization, payload reduction), and quality at speed via CI/CD, automated regression testing, and incremental rollouts in an Agile environment.”

“iGaming product leader with 11 years of Product Owner experience, spanning QA automation (built a testing framework) through BA and ultimately PO for an online poker team for nearly 6 years. Has shipped and managed live web/mobile/tablet games and worked closely with compliance/UKGC on game certification and launches, using BI/data and player feedback to prioritize features and F2P retention mechanics (tournament ticket funnels, quests).”

“Engineering leader who delivered a Magento-to-Shopify rebuild ahead of schedule while maintaining 100% team retention over 4 years at Hydrobuilder Holdings. Also built and ran a concert-listing platform (TourVolume) in production for 12+ years (Webby Honorable Mention) and later open-sourced the full codebase. Deep experience in auth/API platforms on AWS, including moving critical auth services from Lambda to ECS to eliminate cold-start latency.”

“Customer-facing platform support professional focused on application security and reliability for SaaS integrations, with hands-on experience troubleshooting API auth failures and data update issues using Linux/app/DB logs, SQL, and monitoring. Demonstrates strong security fundamentals (least privilege, TLS/access controls, credential rotation) and can design secure AWS agent integrations while also supporting Azure containerized REST API deployments via CI/CD.”

sai anuragh Sangoju

Screened

Mid-level AI/ML Engineer specializing in fraud detection, credit risk, and NLP

Dallas, Texas4y exp

“Built and deployed a production LLM-powered university support chatbot on Azure using a RAG pipeline, focusing on reducing hallucinations, improving latency, and handling ambiguous queries via confidence checks and clarification prompts. Also has hands-on orchestration experience (Airflow/Azure Data Factory), including hardening a demand-forecasting ingestion workflow with sensors, retries, and automated alerts, and uses a metrics-driven testing/monitoring approach for reliable AI agents.”

Mark Wlodawski

Screened

Senior Unity Developer specializing in AI/LLM systems and multiplayer VR

Orlando, FL11y exp

“Backend/data engineer focused on AWS-native Python systems: built a FastAPI microservice on ECS/Fargate serving real-time analytics at millions of daily requests with strong reliability (OAuth2/JWT, retries/timeouts, correlation IDs) and autoscaling. Also delivered Glue/PySpark ETL pipelines to curated S3 Parquet/Athena with schema evolution + data quality controls, owned Airflow pipeline incidents, and has a track record of measurable performance and cost optimizations (e.g., ~80%+ query latency reduction; reduced logging/NAT/Fargate spend).”

“Built a production RAG chatbot for Worcester Polytechnic Institute that indexes 500+ webpages using FAISS + Llama 3, with strong grounding/hallucination controls (confidence thresholds and citations). Also has internship experience orchestrating multi-step ETL pipelines with AWS Step Functions and delivered a 30x faster fraud/claims triage workflow at Munich Re using association rules and stakeholder-friendly dashboards.”

“Built and deployed a production LLM-powered RAG knowledge system to unify operational/policy information across PDFs, wikis, and databases, emphasizing auditability and low-latency/cost performance. Improved answer relevance at scale by moving from pure vector search to hybrid retrieval with metadata filtering and reranking, and partnered closely with healthcare operations/compliance to define acceptance criteria and human-in-the-loop guardrails.”

“QA automation engineer who owned an end-to-end, device-integrated mobile regression suite for Tandem’s insulin-pump-connected mobile app, covering pairing/connectivity/data sync and catching contract mismatches and firmware-related connectivity regressions. Strong in Cypress/JavaScript automation, CI gating in GitHub Actions, and diagnosing production-impacting sync issues using logs and API traces while influencing requirements early to improve testability and UX.”

Ruslan Labza

Screened

Mid-level Frontend/Full-Stack Engineer specializing in React, Angular, and TypeScript

San Jose, CA6y exp

“Built and owned a production data-processing platform feature set (file upload, rule configuration, job execution, results review) using Next.js App Router + TypeScript with Apollo/GraphQL and Zustand. Strong in async job UX (queue/running/failed/completed), durable backend workflow patterns (explicit job states, idempotency), and Postgres query optimization validated with EXPLAIN ANALYZE; also provides post-launch production support and reliability improvements.”

“Candidate has hands-on experience at Cognizant building production-grade automation and integration solutions across Python ML services, Java microservices, Kafka, and Selenium-based UI testing. They stand out for a strong reliability mindset—covering failure modes, observability, flaky test hardening, and translating ambiguous payment-system business processes into resilient end-to-end automated workflows.”

“AI/ML engineer who led Impacter AI’s production deployment of a specialized outreach LLM (CharmedLLM) fine-tuned on GPT-4.1, cutting API costs ~40% while boosting outreach effectiveness ~60%. Built the supporting MLOps and data infrastructure (MLflow, Kubernetes, PySpark, Kafka) and has agentic AI experience from University of Dayton, using LangChain + RAG and vector search (Pinecone) to improve reliability and reduce hallucinations.”