Vetted A/B Testing Professionals

“Full-stack engineer with experience at Zoho and Amazon who has owned production systems end-to-end, including a monolith-to-microservices migration using Kafka and Cassandra that improved search latency ~25% and increased throughput without data loss. Also built a hackathon project (Buildwise) into a sold product for a construction company (AI-driven document compliance checks) and shipped an IoT-based parking availability MVP in 3 weeks.”

“AI/ML engineer who has deployed production LLM/transformer-based systems for merchant intelligence and fraud/support optimization, delivering +27% merchant engagement and +18% payment success. Deep experience in privacy-preserving, PCI DSS-compliant data/ML pipelines (Airflow, AWS Glue, Spark, Delta Lake) and scalable microservices on Kubernetes, plus proven cross-functional delivery in healthcare claims analytics at UnitedHealth Group (12% HEDIS claim reduction).”

“Growth-creative marketer with hands-on paid social and short-form video experience across restaurant and beauty (Tom Ford Beauty). Runs structured creative experiments (Meta A/B ad sets, Meta Pixel conversion tracking) and adapts strategy to platform behaviors (TikTok comments vs IG sharing). Has led creators/editors and drove a reported 100% ROAS lift on a Valentine’s Day TikTok ads iteration.”

“Ticketmaster data engineer who built CDC-driven Kafka pipelines feeding Snowflake for analytics and data science teams. Hands-on in production operations—scaled Kafka during sudden playoff-driven transaction spikes and improved monitoring for preemptive scaling. Known for using small-batch experiments and quantitative metrics to align stakeholders and drive cost-saving architecture changes (e.g., buffering to reduce AWS Lambda invocation frequency).”

“Backend/platform engineer with deep payments experience who built and operated a real-time transaction routing service end-to-end on AWS (Spring Boot, PostgreSQL/RDS, Redis, Kubernetes), delivering ~40% latency reduction and 99.99% uptime via strong resiliency and observability practices. Also productionized an internal LLM-powered RAG knowledge assistant with guardrails and a user-feedback-driven evaluation loop, and has led incremental monolith-to-microservices modernization using Strangler Fig and shadow traffic.”

“Senior growth/partnership leader operating at the intersection of cloud, AI, and creator/gaming ecosystems. Has driven >20% QoQ revenue growth and double-digit user growth via ecosystem partnerships, design-partner pilots, and referral loops, and reports shortening sales cycles 25–30% through a strong telecom/enterprise network (Verizon, Dish, T-Mobile, Scotiabank; earlier Cisco/Ericsson).”

“Growth creative lead at Amazon who ran structured, incrementality-informed A/B tests for Prime acquisition on Amazon DSP. Produced a winning benefit-led video + social-proof framework that improved CTR/CVR while cutting CPA (-24%) and increasing ROAS (+32%), then scaled the approach across email and onsite placements for an additional 10–12% lift in Prime sign-ups.”

“Built a production LLM/RAG assistant for insurance/health claims agents that ingests 100–200 page patient PDFs via OCR (migrated from local Tesseract to Azure Document Intelligence) and delivers grounded claim detail retrieval plus summaries with PII/PHI guardrails. Experienced orchestrating large workflows with Celery worker pipelines and AWS Step Functions (S3-triggered, Fargate-based batch inference/accuracy aggregation), and collaborates closely with non-technical SMEs (claims agents/nurses) through shadowing, iterative demos, and SME-defined evaluation.”

“AI/ML engineer who has shipped both a safety-critical mental health RAG chatbot (Mistral 7B + Pinecone) with automated faithfulness/toxicity monitoring and a deep Q-learning investment recommendation engine at Lincoln Financial Group. Strong in production MLOps and orchestration (AWS Lambda/CloudWatch/SageMaker, Docker, AKS) and in translating regulated-domain requirements (clinical reliability, fiduciary duty) into measurable model constraints and monitoring.”

“Built and shipped a production multi-agent, voice-based conversational assistant for older adults’ daily health management using Vertex AI, FastAPI, Firebase/Firestore, and Cloud Run, with a custom cross-session memory design to keep responses context-aware at low latency. Also partnered with caregivers/elderly users and health officials, translating needs into workflows and explaining HIV risk predictions with SHAP and dashboards.”

“AI engineer at Anote.ai who built and shipped a production multi-agent LangGraph/LangChain/Ray RAG platform for enterprise search and workflow automation, supporting 3 commercial products and 100+ developers. Drove measurable gains (30% accuracy improvement, lower latency) and improved reliability with Redis-based state checkpointing, message-queue synchronization, and Milvus retrieval optimizations, while partnering with PMs/clients to add transparency features like confidence scores and real-time logs.”

“LLM infrastructure engineer who built a production-critical real-time personalization and memory retrieval system for a user-facing product, adding <100ms P99 latency while improving relevance ~20–25% and holding SLA through 3x traffic. Experienced designing tiered retrieval backends (Redis + vector store), deploying on Kubernetes with autoscaling/circuit breakers, and running rigorous observability, incident response, and agent evaluation (shadow traffic, A/B tests, regression/replay).”

“Active in the venture ecosystem as a Rogue Women's Fund fellow and angel investor, with memberships in Gaingels and Angel Squad (HustleFund). Interested in founding a company to leverage extensive experience, and evaluates ideas through market need and economic viability of the target population.”

“Led end-to-end Meta paid social acquisition creative at Daisy, using performance data (CPA/ROAS and funnel drop-off signals) to form hypotheses, ship controlled creative variants, and iterate quickly. Emphasizes early value delivery (first 2 seconds), platform-native execution across Meta/TikTok/YouTube Shorts, and a structured weekly iteration system (readouts, learnings library, naming/versioning) to consistently improve conversion efficiency.”

“Performance marketer with hands-on ownership of $50K+/month spend across Google Ads, Meta, TikTok, and SEO, including healthcare work for Orlando Epilepsy Center. Demonstrated measurable efficiency gains (Meta CPL $300→$90 and 3x ROI) through structured testing, segmentation, and analytics-driven optimization, plus creator strategy improvements on TikTok by shifting to local influencers.”

“Built and shipped production improvements to a Paylocity RAG-based AI assistant, redesigning retrieval into a hybrid HNSW + keyword pipeline and using tuned RRF to fuse rankings—cutting latency by ~2s and reducing token usage by ~5000. Previously spearheaded Apache Airflow integration across ETL pipelines at Acuity Knowledge Partners, creating reusable templates and automated triggers to reduce manual job monitoring.”