Vetted Jenkins Professionals

Anu Baluguri

Screened

Mid-Level Software Engineer specializing in cloud-native microservices and event-driven systems

San Francisco, CA4y exp

“Full-stack engineer with production experience at Atlassian and Zoho, spanning GraphQL federation, React/TypeScript frontends, and cloud-native AWS/Kubernetes operations. Built and operated a federated GraphQL gateway with Terraform + CI/CD + observability, delivering major latency and integration-time improvements, and also designed high-volume Kafka data pipelines (10M+ events/day) with strong reliability guarantees.”

Ranganayak Meravath

Screened

Mid-level Generative AI Engineer specializing in RAG, agentic copilots, and regulated AI

5y exp

“Senior engineer who built and productionized an Azure-based Enterprise AI Copilot for financial/compliance teams, focused on grounded, auditable answers with citations to reduce hallucinations in regulated workflows. Experienced designing multi-step agent orchestration and improving reliability through targeted iterations (e.g., fixing chunking/parsing to materially improve citation accuracy), plus building defensive pipelines for messy ERP/operational finance data.”

Jason Shankel

Screened

Executive Software Engineer/CTO specializing in real-time 3D, game engines, and BIM platforms

San Francisco, CA28y exp

“Game/interactive systems engineer with shipped Unity/C# work (including performance gains on iOS) and experience building creator-facing tooling like a plain-language level scripting system. Also implemented an OpenAI-powered UGC dialogue/event generation pipeline with offline fallback, and built multiplayer collaborative editing in Unreal for an architectural drafting product using checksum + delta synchronization.”

“Full-stack engineer with experience spanning Amazon IMDb and Northeastern’s NeuroJSON portal, combining consumer product work with complex scientific data applications. Built IMDb’s streaming providers feature—described as the company’s most impactful feature of 2023—and has hands-on experience with React/Angular, GraphQL, AWS, Python services, and production monitoring.”

Chitra Uppalapati

Screened

Entry-level Software Engineer specializing in full-stack and machine learning applications

Sunnyvale, CA1y exp

“Built production Python data integrations and dashboard automation for incident analytics, with a strong focus on data quality, observability, and reliability for leadership-facing reporting. Also translated an ambiguous manual creator evaluation process at startup Spring into an automated predictive scoring feature, showing a blend of backend data engineering, test automation, and cross-functional product thinking.”

“Built end-to-end LLM/RAG systems for biological data and scientific literature analysis in a drug discovery setting, helping researchers explore disease insights and treatment hypotheses faster. Combines applied GenAI product work with strong production engineering, including monitoring, retrieval optimization, reusable Python services, and scalable deployment on AWS/Kubeflow.”

“Frontend-leaning full-stack engineer with hands-on experience building financial operations and transaction monitoring products from 0→1 through production scale. They stand out for owning React UI architecture, backend/API integration, and data-layer performance decisions while making pragmatic startup tradeoffs and improving features post-launch based on latency, error, and user feedback.”

Devika gade

Screened

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

Remote, USA4y exp

“Full stack developer with strong implementation ownership across cloud deployments, integrations, and AI-powered support automation. They have put LLM/RAG workflows into production with measurable impact—cutting first response time by nearly 40%—and show unusual depth in debugging non-deterministic AI incidents, improving observability, and turning messy document inputs into reliable API-driven pipelines.”

“Gameplay engineer with hands-on experience across Unreal Engine 5 and Unity, owning systems from level streaming/teleportation to motion-matched character movement. Has shipped/implemented multiplayer features including GAS-based replication with prediction/reconciliation and a deterministic lockstep runner using fixed-point math. Strong at diagnosing hard-to-repro physics issues and balancing performance/feel (e.g., mobile voxel A* pathfinding at 60 FPS, Chaos destruction tuned to avoid trapping players).”

“Robotics-focused engineer who built a non-holonomic self-driving car on Raspberry Pi 5 using ROS 2, implementing sensor fusion (robot_localization EKF), 2D SLAM (slam_toolbox), custom Hybrid A*/RRT* planners, and MPC trajectory tracking. Demonstrated strong real-time debugging and performance tuning (timestamp sync, CPU contention mitigation) and is extending the platform toward CV-based plant identification and autonomous plant watering.”

“Software engineer who owned customer-facing, high-traffic TypeScript/React + TypeScript backend systems end-to-end, emphasizing safe velocity through feature flags, staged rollouts, observability, and rollback-ready incremental delivery. Reports shipping more frequently with fewer production incidents and faster recovery due to these guardrails.”

“Software engineer with experience at PayPal and JPMC building large-scale onboarding/account setup systems using React/TypeScript with Spring Boot/Node microservices and Kafka. Also built an Ignition-based SCADA monitoring tool at Mainspring Energy that became the default for manufacturing/test engineers by aggregating real-time telemetry and historical test data.”

“Backend engineer focused on cloud/distributed systems, deploying Java 17/Spring Boot microservices on AWS EKS with RDS and Kafka. Demonstrated strong production readiness work (DB lock mitigation, Kafka idempotency, gradual rollouts) and delivered a major latency improvement (~400ms to ~100ms). Also has proven cross-layer troubleshooting skills, isolating intermittent API timeouts to a specific Kubernetes node’s network interface issue, and partners closely with ops teams to build dashboards and workflow automation (including Python scripts).”

“Software engineer with primary experience in Java and Python who also troubleshoots and optimizes JavaScript/React performance issues. Has handled customer-reported production problems via log-driven diagnosis and backend workflow fixes, and took ownership of simplifying and automating a service region-expansion process through time analysis and process documentation.”

“Engineering leader who has led 100+ engineers at Sainsbury’s Tech and previously scaled an org from 6 to 60+ at AND Digital. Drove a high-impact modernization of a pricing/decisioning platform serving 1,700 stores—moving from batch monolith to real-time Kafka-based event-driven microservices with MLOps, IaC (Terraform), and zero-trust—delivering £18m+ annual profit uplift and 10+ deploys/day.”

“Worked on payments and wallet transactions, with an emphasis on observability and root-cause analysis. Delivered end-to-end A/B testing optimization and implemented Jenkins-based CI/CD automation that reduced manual implementation to 35% and cut deployments to ~2 minutes, with attention to operational considerations like on-call/call rotations.”

“Backend-focused engineer with experience at AWS building a global alarm processing platform (Python, Lambda/SQS/DynamoDB) handling traffic spikes and reliability issues; resolved duplicate alerts and latency under load by fixing hot partitions and enforcing idempotency. Previously at Cognizant, built Java/PostgreSQL backend workflows for healthcare dashboards using pre-aggregated summary tables, strong SQL optimization, and state-driven job orchestration with ELK-based observability and production guardrails.”

“Senior data engineer with experience in both healthcare (CVS Health) and financial services (Bank of America), building large-scale Azure lakehouse pipelines (30+ EHR sources, ~5TB) and real-time streaming services (Event Hubs/Kafka) for patient vitals. Strong focus on reliability and data quality (Great Expectations, monitoring/alerting, schema drift automation), with measurable outcomes like 50% runtime reduction and 99%+ uptime for regulatory reporting pipelines.”

“Game QA Lead/embedded QA with live production experience supporting a public alpha, owning narrative/early-game content quality and quest progression stability. Known for driving rapid resolution of high-impact blockers via consistent repros, cross-discipline coordination, and data-backed reporting (including bot-based success/failure measurement), while maintaining sprint-aligned test plans and documentation in JIRA/Confluence and leading developer playtests for gameplay feel/polish.”

“Data engineer with Intuit experience owning end-to-end, high-volume financial data pipelines (API/S3 ingestion, Airflow orchestration, Spark/PySpark + SQL transforms, Snowflake marts). Strong focus on reliability and data quality—achieved 99.8% SLA and cut discrepancies by 35% using Great Expectations, reconciliation, schema versioning, and automated backfills; also built near real-time Kafka/API data services with CI/CD and observability.”

“Data/Backend engineer with experience at Naukri building large-scale analytics products over a 130M+ user base, including Spark/Airflow pipelines and Kafka-based clickstream validation with Confluent Schema Registry. Also built an audience segmentation backend (Athena/S3 + Spring Boot APIs) for non-technical internal teams and recently shipped a GenAI customer data audit system (FastAPI/Postgres/Llama) that cut sales-planning validation from ~3 months to ~1 week.”

Shanmukha Koganti

Screened

Mid-level AI/ML Engineer specializing in recommender systems and edge computer vision

Bay Area, CA6y exp

“ML/AI engineer with production experience at Shopify and Intel, building a deep learning product ranking system that lifted add-to-cart ~14% and serving real-time similarity search via FAISS+Redis under <20ms latency at massive scale. Also deployed computer vision models to 100+ retail edge locations using Docker/Ansible/k3s with zero-downtime rollouts, and applies strong MLOps practices (A/B testing, canary/shadow, observability) plus performance optimization (OpenVINO, INT8).”

Pratima Singh

Screened

Senior Full-Stack Software Engineer specializing in FinTech, cloud microservices, and blockchain

Tempe, AZ10y exp

“Python/ML engineer with strong DevOps depth: built an end-to-end regime-aware stock prediction system (custom fine-tuned FinBERT sentiment + technical/macro features) delivering a 12% accuracy lift. Also implemented Kubernetes/Helm + Jenkins/GitHub Actions pipelines (including GitOps-style workflows for multi-cloud Hyperledger Besu) and improved deployment speed/stability by ~50% while addressing race conditions and image drift.”