Vetted A/B Testing Professionals

“Early-stage venture and talent operator with experience sourcing founders and leadership talent, including helping source Truemoringa into a pre-seed investment. Brings a relationship-first style, broad venture-network sourcing, and structured diligence processes spanning product, IP, legal, operations, and cap table review.”

“Candidate mentioned working in a GTM role at Swing Phi, supporting cross-functional efforts around customer segmentation, profiling, and sales pipeline targeting. They cited using Python, SQL, and Excel for data analysis and attributed a 5% increase in acquisition rate to this work.”

“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.”

“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.”

“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.”

Manjory saran

Screened

Senior Backend & Infrastructure Engineer specializing in cloud-native distributed systems

5y exp

“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).”

Pranav Puranik

Screened

Senior AI Engineer specializing in LLMs, RAG, and multimodal NLP

Austin, TX5y exp

“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.”

Shanay Wadhwani

Screened

Mid-level Data Scientist specializing in NLP, computer vision, and applied ML

Washington, DC6y exp

“AI/ML engineer with impactful work for the World Bank across both LLM systems and computer vision, including a PRAI evaluator-assistance platform and a production UNet model for slum detection from multispectral satellite imagery. Earlier built multilingual NLP-based borrower segmentation and credit scoring at Creditmate through its acquisition by Paytm, showing strong experience in ambiguous, high-impact environments.”

“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.”

“Lifecycle/CRM marketer with nearly 7 years at ABC Television, owning end-to-end email execution at high volume while also supporting Braze-based multi-channel programs across email, in-app, and push. Brings strong entertainment/streaming domain experience, using behavioral personalization and A/B testing to improve CTR, watch time, and ultimately ad revenue per user.”

“Primary engineer at Customer Insights AI who built an end-to-end Python pipeline for 340B drug pricing compliance, using ML to detect suspicious pharmaceutical claims and benefit diversion. Stands out for combining healthcare compliance domain knowledge with production reliability practices, and for turning ambiguous analyst-driven review processes into automated workflows that cut manual review by 70%.”

“Internship experience at TikTok and nCino, with hands-on work spanning production Python data pipelines, recommendation-system feature workflows, Salesforce Apex automation, and flaky UI automation for a live stock recommendation platform. Stands out for a reliability-focused approach: anticipating failure modes, instrumenting observability, and turning ambiguous business processes into maintainable automated systems.”

“ML/GenAI engineer with hands-on experience shipping LLM-powered support systems at Uber, including real-time feedback analysis, ticket summarization, and retrieval-grounded knowledge systems. Stands out for combining fine-tuning, RAG, safety evaluation, and production optimization to drive measurable support outcomes like faster handling times, better resolution rates, and lower latency/cost.”

Rucha Joshi

Screened

Junior Software Engineer specializing in full-stack and backend development

Austin, TX2y exp

“Builder of multiple zero-to-one consumer applications, including an anonymous writing feedback tool with a Gemini-powered chatbot, a dietary-profile recipe product using LLM-based substitutions, and a live-updates Sports Hub. Stands out for hands-on full-stack execution, iterative AI experimentation, and a quantified 80% reduction in time users spent finding recipe-compatible ingredients and options.”

Jiajun Huo

Screened

Mid-level Software Engineer specializing in AI, data infrastructure, and LLM systems

Urbana, IL4y exp

“Built end-to-end data and automation systems at Sonic SVM, spanning Python/FastAPI/Kafka/Spark ingestion pipelines, warehouse analytics, and Playwright automation for brittle SSO-protected dashboards. Stands out for combining backend/data engineering with strong observability and reliability practices, plus a pragmatic ability to turn messy manual business processes into measurable self-serve workflows.”

Christopher Kirby

Screened

Executive engineering leader specializing in platform engineering, AI systems, and SaaS

Detroit, MI24y exp

“Senior engineering executive who has repeatedly rebuilt and scaled product engineering organizations in high-growth environments, including restarting Rocket Auto’s stack from scratch and hiring 100+ engineers during StockX’s hypergrowth phase. Particularly differentiated by being unusually hands-on for an executive leader, with active open source work and a strong focus on AI-native engineering workflows, developer automation, and modern architecture transformation.”

“Product leader with a rare cross-industry track record spanning fire departments, supply chain analytics, renewable energy, and staffing. They have led complex zero-to-one and migration-heavy product launches, including shipping 3 new public-safety products during COVID, driving 7x faster customer migrations and major revenue uplift, while also commercializing ML-powered analytics products that increased ARR.”

“Product/design leader in financial services who has driven measurable UX impact at Truist, including moving digital banking visual appeal from 9th to 3rd in JD Power through research-led refinement rather than a costly full redesign. Brings hands-on AI product experience with personalized banking insights, strong stakeholder leadership across complex enterprise environments, and a personal commitment to human-centered AI shaped by tutoring experience and a background overcoming poverty through education.”