Alex – Golang, Kubernetes, AWS

Cloud-native Kubernetes automation and cost-optimization platform used by 2,100+ companies globally, providing workload optimization, automated resource management, rebalancing, and Kubernetes infrastructure intelligence.

• Owned infrastructure-heavy product features end-to-end across technical design, Go controllers, APIs, PostgreSQL changes, Terraform, packaging, deployment, observability, release, and live production verification;
• Delivered APIs for workload, pod, storage, and allocation-group pricing, and migrated legacy ClickHouse queries to a tested query-builder pattern;
• Integrated Karpenter with the platform’s cost-optimization and rebalancing capabilities, refactoring the flow for reuse and testing and helping deliver the customer-facing Karpenter Enterprise release for AWS re:Invent 2025;
• Improved rebalancing safety and performance and built fleet-wide capacity intelligence;
• Built local Karpenter/KWOK infrastructure for validation without remote clusters, establishing fast cloudless KIND/KWOK validation alongside real EKS release gates;
• Designed and shipped the platform’s first umbrella Helm chart, reducing installation from roughly 15 commands to one supported chart;
• Provisioned EKS test environments with Terraform, configured IAM and database access, built image and Helm CI/CD pipelines, and integrated delivery with ArgoCD;
• Added Prometheus metrics, Grafana dashboards, Loki logs, audit events, and incident alerting to support production observability and reliability;
• Introduced Tilt-based debugging, which was later adopted across engineering;
• Resolved production incidents affecting enterprise customer clusters, troubleshooting issues across application and infrastructure layers.

Kubernetes operator for a cloud security platform, automating the scaling of customer cluster nodes to support security workloads across dynamic Kubernetes environments.

• Took a prototype system to production readiness, hardening it for rollout across live customer environments;
• Modernized database access across 4 production Go services, migrating from database/sql to pgx and pgxpool;
• Improved database performance by removing inefficient cascade deletes from cleanup flows and introducing indexing strategies that eliminated full-table scans;
• Refactored and stabilized test suites across 4 services, replacing fragile transaction-based test setups with idempotent patterns and integrating real PostgreSQL and LocalStack containers;
• Established production observability through structured logging, metrics, dashboards, and alerting, including rate-of-change alerts in Grafana;
• Integrated Sentry Performance Monitoring for observability and profiling, and used py-spy to diagnose deep asynchronous bottlenecks in Python services;
• Led response to a critical production incident involving alert delays caused by service autoscaling failures, diagnosing SQS backlog issues and strengthening monitoring around the affected flows;
• Advocated for and successfully drove the deprecation of an unnecessary service, simplifying the production architecture and reducing operational complexity.

Technical consulting for client software projects, from discovery and architecture through team formation and development handoff.

• Led discovery and technical solution design for approximately 50 client pitches, turning business needs into architectures, proofs of concept, estimates, and initial delivery plans;
• Helped convert more than 20% of pitches into active projects and launch 10 engagements;
• Conducted 150+ engineering interviews and helped form delivery teams for new engagements
• Advised clients and internal sales, product, and engineering teams as projects moved from presales into development.

Machine learning capabilities for a C2C classifieds marketplace, focused primarily on image classification, recommendations, and data processing to improve product discovery and user experience.

• Designed and integrated ML solutions into the production classifieds platform, with a primary focus on image classification;
• Developed image classification capabilities for marketplace content;
• Contributed to the development of a recommendation system for classifieds listings;
• Built data processing pipelines supporting ML model development and inference.