Vetted Go Professionals

“Hands-on engineering manager at a marketing company leading a highly senior, distributed team (10 direct reports) while personally coding ~60–70% and owning end-to-end architecture across three interconnected products. Built agentic CRM automation and a reinforcement-learning-driven distribution layer for channel spend/bidding, with a strong focus on scalable design and observability (Prometheus/APM/logging) enabling frequent releases and few production incidents.”

“Software engineer with ~2 years at UnitedHealth Group plus CMU coursework/TA experience, spanning backend modernization and cloud-native operations. Worked on migrating a customized open-source EDI system from Python 2 to Python 3 while improving SQLite database traceability via JSON exports, and has hands-on Kubernetes microservices deployment on Azure using Helm, HPA, and Jenkins-based Git-triggered CI/CD. Also built a large-scale real-time ride-hailing simulation using Kafka + Samza with explicit fault-tolerance strategies.”

“Backend/platform-focused engineer who builds scalable onboarding and data ingestion pipelines for complex client data formats, emphasizing staged validation, idempotent job boundaries, and safe rollouts behind feature flags. Strong in production diagnostics (Kibana/Logstash, SQL, debugger traces) with a concrete example of finding a regression causing incorrect Tax Loss Harvesting alert counts within a day, and experienced enabling both engineers and customer-facing teams through docs, runbooks, and technical walkthroughs.”

“Backend/data engineer focused on production ML/LLM systems: built a real-time FastAPI inference API on Kubernetes with strong reliability patterns (timeouts, idempotent retries, centralized error handling). Delivered AWS platforms using EKS + Lambda with GitHub Actions/Helm CI/CD and built Glue-based ETL from S3/Kafka into Snowflake with schema evolution and data-quality controls; also modernized legacy analytics/recommendation workflows into Python services with safe, feature-flagged cutovers.”

“Amazon Alexa engineer who architected and shipped a GenAI Knowledge Agent used by 2M+ customers, focused on making LLM outputs auditable via citations and a verification layer that prevents hallucinations. Built the full vertical slice (FastAPI/LangChain backend + React/TypeScript streaming UI) while keeping p99 latency under 200ms, and has proven incident response experience on AWS (Lambda/DynamoDB scaling issues).”

“AWS intern who significantly evolved a Drift Audit Service backend (Control Tower/EventBridge context) to make drift findings more explainable and reduce false positives by adding a verification step in Lambda before event ingestion. Demonstrates strong API design fundamentals in Python/FastAPI (contracts, idempotency, security controls) and careful rollout practices (feature flags, canaries, phased deployments).”

“Customer-facing technical professional with Amazon incident-management experience who helps drive adoption of complex ML/LLM solutions by delivering hands-on demos and rapid model fine-tuning. Applies a disciplined debugging approach (repro + logs/metrics + severity triage) and maintains runbooks to resolve SEV2 issues in ~1 hour, while also partnering with sales/customer teams to ship patches and new features based on feedback.”

“TikTok engineer (4 years) who built and owned multiple ad transparency platforms used by internal teams and advertisers worldwide. Strong full-stack profile spanning Next.js/TypeScript + Redux frontends, a secure/optimized BFF layer, and event-driven backend workflows (Kafka, retries/DLQ, Redis idempotency) with heavy emphasis on observability and performance; cites a 20% moderation efficiency gain on a modernized legacy tool.”

“Senior engineering leader with experience at Cisco, Amazon, and startup Shopkick, operating at high scale (e.g., Secure Web Gateway handling ~40M QPS). Known for measurable impact across reliability and cost (85% efficacy improvement; Datadog spend cut from ~$500k/month to ~$15k/month) and for leading complex platform modernization (1-year monolith-to-microservices/event-driven migration with zero customer impact) plus compatibility-focused API design that cut device onboarding from a month to a day.”