Vetted Jenkins Professionals

“Software engineer focused on data platforms and applied LLM systems: built an internal data quality monitoring layer to catch silent data drift and iterated post-launch after finding ~30% false-positive alerts, reducing noise via dynamic baselines and improved structured logging. Also shipped a production RAG-based internal knowledge assistant over Jira/Confluence with citations, confidence-based fallbacks, and nightly automated evals to prevent regressions.”

“Data engineer focused on large-scale ETL/ELT pipelines across cloud stacks (GCP and AWS), including Spark-based transformations and orchestration with Airflow. Has experience loading up to ~2TB per BigQuery target table and designing atomic loads to multiple downstream systems (Elasticsearch + Kafka), with Kubernetes deployment and Jenkins CI/CD.”

“Backend/full-stack engineer (5+ years) with Shopify experience integrating LLM/RAG workflows into production APIs. Owned a Python TensorFlow Serving inference pipeline connected to Java microservices via gRPC, optimizing tail latency at ~10k concurrent load and improving retrieval relevance with embedding and evaluation work. Strong Kubernetes/EKS + GitOps/CI/CD background, including monolith-to-microservices migrations and event-driven streaming patterns.”

“Backend engineer with experience at UnitedHealth Group redesigning a high-traffic Spring Boot microservice from blocking to reactive architecture during peak season, cutting median latency by 47% for a service used by ~10M customers annually. Strong in Kubernetes-based deployment/scaling and pragmatic rollout strategies (blue-green/incremental traffic shifting) with performance and database troubleshooting.”

“Backend/data engineer from ASML who modernized a legacy SAS-based statistical processing system into a cloud-native AWS platform (Lambda/FastAPI, Step Functions/EventBridge, Glue, S3/RDS) with strong reliability and data-quality practices. Demonstrated measurable performance wins (RDS query reduced from 90+ seconds to <5 seconds) and hands-on incident ownership for production ETL pipelines.”

“Teradata Text Security intern who built a production LLM-powered planner agent that decomposes complex tasks into dependency-aware subtasks (DAG/topological graph) and executes them via a custom orchestrator with parallelism, status tracking, and error handling. Also contributed to an HR-facing internal document chatbot concept to streamline onboarding, showing cross-functional collaboration.”

“Amazon experience integrating LLM-powered chat automation into Amazon Connect contact-center workflows, taking prototypes to production with compliance-minded guardrails, schema/policy validation, and robust fallbacks. Regularly supports rollout and adoption via developer workshops, integration guides, and customer calls, with strong production triage and observability practices.”

“Robotics software engineer who built a targeting/payload delivery module for an FPV drone, integrating GNSS/IMU and other sensors with an EKF-based fusion stack and multi-rate synchronization. Also designed a servo gimbal with a laser ToF sensor to validate predicted landing locations using DH-based forward/inverse kinematics, leveraging ROS2/Gazebo for simulation and Python/MATLAB for filter tuning.”

“Backend engineer who built a real-time pipeline for recording, transcribing, and analyzing audio from 400+ news radio stations, scaling Whisper on an HPC cluster with 7 H100 GPUs. Has strong performance optimization experience (30% latency reduction via SQL/query design; 50% DB call reduction via Redis caching) and has implemented region-based data isolation and PII protections in a regulated environment (JP Morgan Chase).”

“Backend engineer from Palantir who built and productionized an enterprise LLM-based document intelligence/search platform, evolving it into a hybrid lexical+vector retrieval system. Emphasizes reliability and cost control via strict LLM gating, robust fallback paths, and evaluation frameworks (e.g., MMLU/BLEU), plus disciplined migration practices (feature flags, dual-writes, shadow reads) to ship changes safely at scale.”

“Built a production LLM/RAG assistant for insurance/health claims agents that ingests 100–200 page patient PDFs via OCR (migrated from local Tesseract to Azure Document Intelligence) and delivers grounded claim detail retrieval plus summaries with PII/PHI guardrails. Experienced orchestrating large workflows with Celery worker pipelines and AWS Step Functions (S3-triggered, Fargate-based batch inference/accuracy aggregation), and collaborates closely with non-technical SMEs (claims agents/nurses) through shadowing, iterative demos, and SME-defined evaluation.”

“Infrastructure/operations engineer with hands-on IBM Power/AIX administration (LPAR/DLPAR, HMC, RMC) and PowerHA cluster failover experience, plus modern DevOps tooling across CI/CD, Kubernetes/Helm, and IaC (Terraform/CloudFormation/Ansible). Emphasizes controlled change management, drift prevention via Git-as-source-of-truth, and observability practices using Prometheus/Grafana.”

“Capital One engineer leading the architecture and delivery of a large-scale AWS Glue/Spark/Delta Lake batch messaging pipeline that decoupled batch from real-time flows, added multi-region failover and automated retries, and delivered ~40% AWS cost savings with ~3x performance gains. Currently building an LLM-powered Slack bot using RAG to automate message investigations by querying CloudWatch, Snowflake, and internal documentation with privacy-aware masking of NPI/PII.”

“Backend/data engineer with production experience building credit/fraud enrichment services and checkout pipelines on AWS (EKS + Lambda) using FastAPI, Kafka, Postgres, and Redis, with a strong focus on reliability patterns (timeouts/retries/circuit breakers) and observability. Has also built AWS Glue/PySpark ETL into S3/Redshift with schema evolution and data quality controls, and modernized legacy credit decisioning into Java/Node microservices with parallel-run parity validation and feature-flag rollouts.”

“Built and deployed a production AI/ML SRE copilot that uses RAG over real-time Splunk signals plus deployment/runbook data to generate grounded incident summaries and next steps, cutting time-to-contact by 30%. Treats the knowledge corpus like a production dataset (quality gates, semantic chunking, metadata enrichment) and runs golden-dataset automated evals to ensure reliability, while partnering closely with ops/support leaders through discovery sessions and metric-driven demos.”

“Engineering leader at Bayer Crop Science leading a Core Platform team responsible for widely used open-source TypeScript/React and mobile SDKs (npm/GitHub) embedded across 10M+ monthly active devices. Known for shipping high-performance, backward-compatible developer frameworks with rigorous release discipline (bi-weekly releases, 99.99% uptime, long streaks of zero breaking changes) and major DX wins (onboarding cut to minutes, support tickets down 82%).”

“Engineering leader who managed a 20-person cross-functional team building customer-driven software solutions, delivering a 50% reduction in simulation/test lifecycle and securing a long-term strategic SLA. Strong in scalable data ingestion architectures (FastAPI + Kafka + multiprocess workers), operational diagnostics (correlation IDs/centralized logging), and microservice decoupling for analytics/visualization. Active open-source contributor who shipped a NATS bug fix and improved SDK onboarding with automation that cut ramp time by 30%.”

“Technology leader with experience owning enterprise roadmaps and executing large-scale platform standardization during rapid M&A—most notably driving a tech roadmap across a 37-company portfolio at Regent, tackling technical debt and security gaps via unified cloud-native architecture, IAM/logging, CI/CD, and a global SRE model. Previously scaled an Adobe engineering org from 8 to 40+ across four regions, implementing clear org design, KPIs, and an extreme-ownership culture to support 24/7 operations and enterprise needs.”

“Backend-focused engineer with hands-on experience modernizing a legacy SNMP/PNM data collection system at CableLabs into a cloud-accessible Kubernetes pipeline, feeding Prometheus-formatted metrics into VictoriaMetrics and visualizing real-time network health in Grafana for 100+ modems. Also built a FastAPI + Supabase appointment booking portal for a clinic with encryption and phone-number-based auth, and has frontend experience debugging S3-based HEIF image rendering issues.”

“Cloud/platform engineering lead with deep Azure AKS and SRE/observability expertise who migrated an EY enterprise SaaS platform from monolith to cloud-native microservices, supporting 10+ products and ~$200M annual revenue with ~99.9% uptime. Also building an open-source Kubernetes-native AI agent orchestration platform (AgScale) in Go with CRDs/controllers, policy/tool governance, token budgets, and production-grade monitoring.”