Vetted Software Developers

“Engineering leader/player-coach who built and validated a preference-based recommendation engine using clustering, including generating test data to evaluate how clusters evolve over time. Has SRE/DevOps experience and has owned production incidents end-to-end (logging-driven RCA and refactoring patterns that failed at large data scale). Emphasizes quality and platform stability via unit, integration, and load testing, and has managed performance via regular 1:1s and PIPs.”

“Fintech product builder focused on AI-native opportunities; recently helped their company operationalize LLMs in customer service and bank ops by creating systems to continuously improve prompts and evaluations. Also drove growth by identifying hooks in a major American retailer distribution channel and integrating into the retailer’s payment flows to become a key part of the user funnel.”

“Meta engineer who owned a heavily used internal goals/performance management feature end-to-end, driving major responsiveness improvements by restructuring frontend data loading and adding backend caching (Memcached), cache warmups, and query/index tuning. Strong focus on production quality: observability, error monitoring, and improving test coverage to prevent regressions during peak review cycles.”

“Engineering/tech leader with experience spanning major platforms (mentions Microsoft and AWS) and leading ML-driven product architecture (ranking systems). Describes driving a shift to a layered, API-standardized service architecture (including vector database components) that materially increased delivery speed (weeks to hours) while improving scalability and security, and emphasizes rigorous execution reviews (QDR/OKRs) plus transparent remote-team operating rhythms.”

“Serverless-focused backend/data engineer who has delivered production Python services on AWS (FastAPI on Lambda/API Gateway) plus Glue-based ETL pipelines from S3 to relational databases. Strong in operational reliability (timeouts, retries, monitoring/alerts) and modernization work, including parallel-run parity validation for migrating legacy batch logic to Python services. Demonstrated measurable SQL tuning impact (15 min to under 3 min).”

“Platform/backend engineer focused on Kubernetes at scale: built a Java control-plane service for multi-region cluster provisioning/monitoring/upgrades using Kafka-driven async workers, and solved peak-load provisioning failures by eliminating blocking I/O and dynamically scaling consumers. Also shipped an LLM-assisted Kubernetes troubleshooting/remediation feature that pulls Prometheus logs/metrics into prompts and uses guardrails (confidence thresholds + human-in-the-loop) to prevent risky actions.”