Vetted Argo CD Professionals

“Backend engineer who has led major platform evolution to cloud-native microservices (Spring Boot on AWS with Terraform) and built scalable, secure FastAPI APIs. Demonstrates strong production rigor with metric-driven validation, canary/phased rollouts, and incremental migrations using shadow traffic/feature flags/parallel writes—achieving faster deployments, fewer incidents, and zero-downtime traffic spikes and migrations.”

“Backend-focused Python/Flask engineer who has built authentication/profile services with clean modular architecture (blueprints + service layer) and tuned SQLAlchemy/Postgres for scale using indexing, query rewrites, and pagination. Has production-style integration experience for AI/ML via TensorFlow Serving and OpenAI APIs (batching, rate limiting, caching), plus multi-tenant data isolation and high-throughput background processing with Celery/Redis and idempotent jobs.”

“AIX/IBM Power Systems engineer with hands-on production incident leadership in a regulated banking environment, using deep OS-level tooling to diagnose CPU entitlement and memory pressure issues. Experienced with HMC/vHMC, VIOS, and zero-downtime DLPAR resizing, plus PowerHA/HACMP clustering and validated failover testing. Also drives migration readiness via Bash/Python automation (60% manual-effort reduction) and phased AIX cloud/hybrid cutovers.”

“Backend/platform engineer who built an AI RAG system on FastAPI/Postgres/AWS with 10+ microservices, vector search optimization (ANN + two-stage re-ranking), and GitOps-driven CI/CD that cut deploy time from hours to minutes. Also deployed Java identity services on Kubernetes at TSMC for 200K+ users using ArgoCD/Azure Pipelines, and built a reliable real-time IoT pipeline (MQTT/Node/MongoDB) with strong consistency controls.”

“Platform-focused engineer experienced in productionizing ML/LLM systems: containerized a local prototype, implemented CI/CD, deployed to Kubernetes with scaling controls, and added monitoring/logging. Comfortable diagnosing real-time issues in LLM/agent workflows using logs/metrics and incident stabilization tactics, and supports sales calls by clearly explaining production scalability to unblock customer decisions.”

“Infrastructure reliability/capacity-focused engineer with hands-on IBM Power/AIX (LPAR/DLPAR, HMC, VIOS) performance troubleshooting and modern cloud-native delivery experience. Built production CI/CD and Terraform-managed AWS/EKS environments, and has led real incident recoveries spanning Kubernetes autoscaling and AWS quota constraints with concrete RCA and prevention improvements.”

“Software engineer at Capital One who owned and shipped AI-driven personalization and internal insights dashboards end-to-end, emphasizing fast iteration with feature flags and tight user feedback loops. Built a TypeScript/React + Spring Boot/Python document automation platform with compute-heavy NLP microservices, async workflows, and production-scale reliability/performance practices (Kafka/RabbitMQ-style queues, Redis caching, tracing).”

“Backend engineer who built and owned an AI-powered SMS survey platform for a nonprofit serving at-risk communities (internet-limited users), using Cloudflare Workers + Twilio and a state-machine survey engine. Scaled it to ~10k active users with near-zero downtime, added English/Spanish support, and iteratively improved LLM behavior (Claude 3.7 Sonnet) to handle nuanced, real-world SMS responses reliably.”

“AI/ML engineer who has shipped production AI systems end-to-end, including an automated multi-channel (Gmail/WhatsApp/voice) candidate interviewing workflow and an enterprise RAG knowledge search platform. Demonstrates strong production rigor (monitoring, A/B tests, guardrails, schema validation, shadow testing) with quantified impact: ~60–70% reduction in interview evaluation time and ~20–30% relevance gains in RAG retrieval.”

“Infrastructure-focused engineer with Vonage experience modernizing early-stage cloud architecture (Terraform modularization, blue-green deployments, containerization, and zero-downtime database migration planning to Aurora). Also built a local end-to-end side project, Vastu AI, combining a custom-trained YOLO model (Roboflow-labeled data) with a locally hosted LLM via Ollama to generate a vastu compliance report from floor-plan images.”

“Software engineer with strong end-to-end ownership of search and listing systems (React/TypeScript frontend with Node.js + Spring Boot backends), focused on shipping fast while managing risk via feature flags, testing, and metrics. Demonstrated measurable UX/performance wins (reduced latency and search abandonment) and built internal observability tooling (dashboard + alerts) that improved incident response. Experienced with microservices reliability patterns including idempotency and dead-letter queues.”

“GenAI/LLM engineer with production deployments in both fintech and retail: built an AI-powered mortgage document analysis/automated underwriting pipeline at Fannie Mae (OCR + custom LLM) cutting underwriting review from 3–4 hours to under an hour with privacy-by-design controls. Also helped build Sephora’s GenAI product advisory bot using LangChain-orchestrated RAG (Azure GPT-4, Azure AI Search, MySQL HeatWave vector search), focusing on grounding, evaluation, and compliance-aware architecture choices.”

“Backend/DevOps-focused engineer with healthcare and financial systems experience, including an ICU readmission risk platform delivering real-time ML scores via a secure FastAPI service (PyTorch model serving, PostgreSQL, Celery/Redis) deployed on AWS with strong observability. Has hands-on Kubernetes GitOps delivery (Helm, ArgoCD, HPA) and has supported a JPMC on-prem-to-AWS microservices migration using phased validation and blue-green cutovers, plus Kafka/Avro streaming for real-time transaction processing.”

“Hands-on technical professional experienced in taking LLM/AI-adjacent integrations from prototype to production, using customer observation to refine UX and uncover edge cases. Diagnoses workflow issues in real time using logs and Sankey-style workflow analysis, and communicates fixes with clear short/long-term plans plus proactive alerting. Also partners cross-functionally to drive adoption and cost savings, including a POC around IBM Sterling Integrator that reduced licensing costs by $30K/year.”

“DevOps engineer focused on CI/CD who built and productionized LLM/MCP-based chat agents integrated into Cisco Webex to help developers troubleshoot PRs and pipelines via GitHub/Jenkins data. Strong in operationalizing agentic systems with observability (OpenTelemetry/Grafana), user-scoped rate limiting, and Kubernetes-based scaling, and has presented demos on agent SDK capabilities and DORA metrics dashboards.”

“CTO-for-equity founder who partners with non-technical co-founders to bring AI-powered product ideas to market, emphasizing financial viability and go-to-market planning over "just an MVP." Currently working with two other founders (CEO/Sales and CPO/industry expert) to launch a SaaS platform, leveraging AI coding tools (Cursor/Windsurf) for extremely fast, production-ready iteration with daily releases.”

“IBM Power/AIX engineer with hands-on ownership of large AIX 7.1/7.2 environments (VIOS, HMC/vHMC) supporting enterprise middleware/back-end workloads. Demonstrated real production incident handling: identified CPU entitlement underprovisioning after a DLPAR change and restored performance via live CPU rebalancing, plus PowerHA failover execution and runbook/process hardening. Also builds secure CI/CD pipelines (Jenkins/GitLab/Azure DevOps with CyberArk) and Terraform IaC with drift management and controlled rollouts.”