Vetted GitLab CI Professionals

“Data scientist at Guardian Airwaves building a RAG-powered quiz generator using Grok AI, with hands-on experience solving hard document-ingestion problems (PDFs with images/tables) via unstructured.io and LlamaIndex. Has deployed production systems on AWS EC2 and brings a pragmatic approach to agent reliability (human-in-the-loop, LLM-based eval, latency/cost metrics) while effectively translating RAG concepts to non-technical stakeholders.”

“Built a production agentic AI assistant in Python using Playwright plus Google Gemini’s vision capabilities to automatically document and execute UI workflows step-by-step, reducing developer time spent on trivial documentation/knowledge transfer. Also built an Apache Airflow ETL pipeline and has experience evaluating AI agents with human-in-the-loop methods, plus successfully communicated a vision-model-based CMS analytics PoC to non-technical university stakeholders and proposed it to Academic Technology with cost-savings rationale.”

“Backend/data engineer who built an enterprise LLM assistant (AI Genie) at Broadband Insights using a LangChain + GPT-4 + Pinecone RAG pipeline to automate broadband analytics reporting. Developed Python/Dagster ETL processing 10M+ records/day and improved data freshness by 60%, with production-grade scalability patterns (async workers, containerized microservices, Kubernetes) and strong multi-tenant isolation practices.”

“Frontend lead on an SME CRM for a bank, building a scalable multi-country/multi-product React/Next.js platform with a config-driven onboarding workflow and multi-role permissions. Emphasizes quality and maintainability through CI gates, a full testing pyramid, and disciplined server-state caching with RTK Query, plus feature-flagged rollouts and data-driven iteration from pilot user feedback.”

“QA automation engineer focused on backend/API quality who owned an end-to-end API regression suite and integrated Cypress/JS automation into GitLab CI with smoke-vs-nightly regression gating. Caught a critical auth security regression (expired tokens returning 200 instead of 401) before production and is strong in stabilizing flaky tests using network interception and actionable CI reporting.”

“End-to-end engineer focused on AI-native enterprise systems, including a production generative knowledge platform using RAG + semantic search over internal documentation (React, Python/Flask, GPU-hosted NLP models, Pinecone) with strong CI/CD and observability. Reports concrete outcomes including 40% faster knowledge access and ~75% employee adoption, and has led incremental cloud-native modernization using feature flags, parallel runs, canary releases, and regression testing.”

“Backend/data engineer with strong production experience across Python microservices (FastAPI) and AWS serverless/data platforms (Lambda, API Gateway, Glue, Redshift). Demonstrates reliability and incident ownership (rate limits, retries/circuit breakers, monitoring) and has delivered measurable SQL performance gains (12–15s to <800ms, ~60% CPU reduction). Seeking fully remote work and not open to relocation/onsite meetings.”

“Frontend engineer focused on building and scaling data-heavy, real-time dashboards with React/Next.js/TypeScript. Emphasizes performance and reliability at scale through modular architecture, centralized state (Zustand/Redux), strict API contracts, automated testing, and production monitoring (Grafana/CloudWatch), and has experience shipping quickly with feature-flagged rollouts and rapid iteration from user feedback.”

“QA automation-focused candidate with hands-on ownership of unit and integration test suites, including CI/CD integration in GitLab. Caught a database-query regression that would have shipped incomplete API data by relying on automated integration tests, and has practical Cypress experience stabilizing flaky tests using cy.intercept()/cy.wait() and stable selectors.”

“Backend developer (recent co-op at Ticker) building and architecting financial backend services with near real-time data needs, including third-party API integrations. Improved performance and reliability via Redis caching (tiered refresh + TTL) and PostgreSQL query tuning (EXPLAIN ANALYZE + composite indexes), and has exposure to AI-agent/RAG concepts for validating stock-market information against trusted sources.”

“Backend/data engineer with hands-on production experience building a real-time notification API on Flask/Celery/Postgres and scaling it on AWS with Docker, Redis queuing, and SQLAlchemy query optimization. Also delivered AWS serverless deployments (Lambda) using Terraform + GitHub Actions and built AWS Glue ETL pipelines from S3 to Redshift with CloudWatch monitoring and DataBrew data quality checks.”

“Backend/data engineer with hands-on production experience across Python/Flask microservices and AWS serverless/data platforms (Lambda, DynamoDB, S3, Glue/PySpark). Demonstrated strong reliability and operations mindset (JWT/RBAC, retries/timeouts/circuit breakers, CloudWatch/SNS alerting) and measurable performance wins (SQL report runtime cut from 10 minutes to 30 seconds). Seeking ~$150k base and cannot travel for onsite meetings for the next 5–6 months due to family medical constraints.”

“Paid media performance marketer managing $50K+/month spend across Meta and Google for eCommerce and lead-gen, with a strong creative-testing orientation (UGC/video vs static) that produced ~25–30% lower CPA and ~35% higher ROAS when scaled. Builds full-funnel systems across Meta/TikTok (demand gen) and Google Search/PMax (high-intent capture), using marginal ROAS/CPA, frequency-based fatigue signals, and statistically grounded testing to scale or cut campaigns.”

“Software engineer experienced delivering customer-facing, real-time industrial monitoring dashboards (motors/shafts/turbines) by partnering directly with end users to refine charts, alerts, and performance. Strong in API/platform integrations and production troubleshooting—uses feature flags, logging, validation/mapping, containerization, and performance testing to keep systems stable while iterating quickly.”

“DevOps engineer (State Farm) with hands-on ownership of Python backend services and data pipelines, deploying microservices and workers on Kubernetes using GitOps (Argo CD). Has led complex cloud-to-on-prem/hybrid migrations with staged cutovers and rollback planning, and built Kafka-based real-time streaming pipelines with schema governance, autoscaling, and strong observability.”

“Robotics software engineer focused on perception/SLAM and systems integration, recently built a quasi-dynamic mapping pipeline to track and reconstruct articulated objects (e.g., drawers) from RGB video using SAM2, COLMAP SfM, and 3D Gaussian Splatting. Also has strong ROS2 sensor-pipeline experience (custom messages, MCAP rosbag deserialization, tf2) and demonstrated real-time performance tuning by accelerating an ICP-based LiDAR SLAM component ~30x (from ~3s to <100ms per frame).”

“Built and shipped both a solo real-time multiplayer Spades game (TypeScript monorepo with shared client/server engine) and a production internal LLM-powered document Q&A tool for a SaaS company. Demonstrates strong RAG pipeline design (Pinecone + embeddings + reranking), rigorous eval/regression practices, and pragmatic data ingestion/observability work across Confluence, Notion, and messy PDFs/OCR—backed by clear metric improvements (P@1 61%→78%, escalations 40%→22%).”

“Backend engineer with experience modernizing high-traffic subscription and payment systems (TCS) by moving to event-driven Spring Boot microservices with Kafka, adding idempotency/state management to eliminate duplicate processing. Built and scaled FastAPI services for AI automation workflows (360DMMC) with versioned contracts, JWT security, and strong observability, and has led live refactors using feature flags, parallel runs, and data reconciliation.”

“Backend/data engineer with hands-on production experience building Python/Django APIs on PostgreSQL and delivering AWS serverless + containerized architectures (API Gateway/Lambda, IaC, CI/CD, secrets/config). Has operated AWS Glue pipelines ingesting S3 log/3rd-party data with schema evolution monitoring, modernized legacy batch logic into API-based services via parallel-run parity testing, and improved Postgres query performance by several seconds; prefers fully remote work and targets $120–130k base.”

“IBM Power/AIX engineer who has owned a 150+ LPAR AIX 7.x estate with VIOS/HMC/vHMC and PowerHA in production, including real outage and failover recoveries. Also brings modern DevOps/IaC experience—built Jenkins pipelines deploying to AKS and implemented Terraform on AWS with remote state, locking, and drift management.”

“Backend engineer with Accenture and EY experience building multi-tenant financial/compliance platforms in Python/Flask. Strong in performance and scalability work across SQLAlchemy/PostgreSQL (EXPLAIN ANALYZE, indexing, N+1 fixes) and in reliability improvements using Celery + Redis. Has integrated external AI model APIs for document extraction/invoice validation with robust background processing, retries, and output cleaning.”

“Co-founder at Skarbe who built “Oskar,” an autonomous sales agent that handles inbound email, lead qualification, and automated follow-ups using a multi-agent architecture (OpenAI Agents SDK) with a human-in-the-loop learning phase for reliability. Also owned scaling and reliability of Gmail/Outlook sync, including a Node.js-to-Rails migration and incident response during a Product Hunt launch that generated hundreds of signups and a ~2M-email queue.”

“QA automation engineer with hands-on ownership of both UI and API test automation, including building an API test module from scratch to validate all Swagger-exposed endpoints with positive/negative coverage and pairwise optimization. Experienced stabilizing flaky Cypress tests through improved selectors (data-cy) and API-call synchronization, and integrating tiered test suites into GitLab CI with merge/release gates plus JUnit/HTML reporting and Slack notifications.”