Vetted Agentic AI Professionals

“Cloud-focused engineer experienced deploying and stabilizing complex production systems that span APIs, infrastructure, and automated workflows, with a strong observability and safe-release mindset (feature flags/canaries/rollbacks). Has hands-on, customer-facing incident leadership, including executing DR regional failover during an AWS us-east-1 outage to maintain service and reportedly save a client ~$10M.”

“ML/NLP practitioner with experience building an embedding-based ad matching and search system at Vericast (BERT embeddings + similarity search) to replace a third-party taxonomy approach, evaluated via a human-curated gold standard. Also built a custom NER pipeline at Allstate for auto accident claims calls using a bidirectional LSTM and achieved 90%+ F1, with a strong emphasis on production-grade ML workflows (testing, CI/CD, orchestration, versioning, validation).”

“Insurance-tech CTO and repeat founder with 10+ years in insurance startups; was employee #4/CTO at Polly (formerly DealerPolicy) and helped scale it from a PowerPoint to 250 employees while raising $180M+. Currently building and selling AgentCanvas.ai—an extensible AI accelerator platform for large insurance agencies—after coding the product end-to-end and now running demos/POCs with prospective buyers.”

“LLM engineer who built a production seller-support RAG system at eBay using hybrid retrieval (BM25 + Pinecone vectors) with Cohere reranking, LangGraph orchestration, and citation-grounded answers. Strong focus on reliability: semantic/structure-aware chunking, automated Ragas-based evaluation with nightly regressions, and production observability (LangSmith) plus drift monitoring (Arize). Also implemented a multi-agent fraud pipeline with AutoGen using JSON-schema contracts and explicit termination conditions.”

Anvith Reddy Dodda

Screened

Mid-level AI Engineer specializing in GenAI, NLP, and MLOps

Remote, USA3y exp

“LLM/agentic-systems engineer with PayPal experience hardening an LLM-powered fraud support assistant from prototype to production, focusing on low-latency distributed architecture, rigorous evaluation/testing, and security/compliance. Comfortable in customer-facing and GTM contexts—runs technical demos/workshops, builds tailored pilots, and aligns sales/CS with engineering to close deals and drive adoption.”

Dylan Tang

Screened

Intern Software Developer and ML Researcher specializing in medical imaging and computer vision

Chicago, IL0y exp

“AI/ML practitioner with experience spanning audio/LLM applications (built "Iota" using Whisper, tiktoken, and a local Ollama-served LLM) and healthcare ML (Facemed.ai; UChicago Radiology). Demonstrates a production-oriented mindset—focus on data/model fit, deterministic field testing, and operational safeguards—and has improved research evaluation workflows via a hash-table-based concurrent model tracking approach.”

jitender Hooda

Screened

Executive Client Partner specializing in engineering and digital services

San Ramon, CA19y exp

“Founder building an agentic AI-based low-code platform for B2B enterprise applications, validated through enterprise client conversations and delivered via rapid paid MVP/POCs. Platform has seen production traction (6–7 apps, 1000+ daily users) and includes capabilities like QR scanning integrated with ERP/PLM systems. Experienced in business development and client relationships, with a pragmatic, ROI- and speed-focused approach to product and GTM under tight capital constraints.”

Sandeep Mekala

Screened

Director-level Mobile Engineering Manager specializing in Generative AI and agentic mobile experiences

Remote13y exp

“iOS player-coach who led end-to-end development of real-time customer support chat and unified notification systems for T-Mobile’s iOS app using SwiftUI, Firebase, WebSockets, and Core Data (including offline handling). Drove measurable reliability/latency gains (~30%) through a major notification refactor and owned a high-severity push-notification incident from rollback through RCA and backward-compatible hotfix, while also scaling team process and people management.”

“30-year Silicon Valley startup veteran who built Pratexo, an intelligent edge analytics company focused on the energy transition, raised $15M in seed funding, and landed a major partnership with ABB. He has spent the last decade continuously advising startups and brings deep familiarity with VC and accelerator ecosystems including YC and ABB's SynerLeap.”

Richard Bemis

Screened

Executive CIO/CTO/CDO specializing in data, AI/ML, and digital transformation

Long Beach, CA21y exp

“Founder building a healthcare provider data management startup who has progressed from problem identification to product architecture, patent filing, prototype development, beta customer outreach, and angel fundraising. They also have experience performing technical assessments for VCs and approach company-building with a structured focus on customer demand, risk mitigation, IP protection, and candid core-team formation.”

Devang Shah

Screened

Executive AI and Cloud transformation leader specializing in enterprise GTM and product engineering

San Jose, CA23y exp

“Candidate is interested in building horizontal AI infrastructure capabilities, specifically around observability, and brings exposure to investor evaluation dynamics from experience at PE-backed firm WinWire. They appear strongly motivated by entrepreneurial ownership, creativity, and the ability to drive and pivot ideas in a venture studio or startup environment.”

“Seasoned entrepreneur with decades of cross-functional business experience who initially expected a CTO role at an existing company rather than a founder track. Brings a distinctive mix of technical scalability thinking, complex integration awareness, education/multimedia production capability, and formal credentials including a PhD, security clearances, and AI and leadership certifications.”

“Enterprise account leader in Kazakhstan (Procter & Gamble context) managing a $11M strategic retailer account and a broader book of 40 accounts/900 stores. Known for data-driven dashboards and cross-functional execution to prevent churn, drive e-commerce growth, and deliver measurable lifts (e.g., 100% SKU retention, +190% e-com growth, +45% pilot sales lift). Upskilling into martech/analytics and AI automation (Power BI, SQL, Python; CS50 and AWS Cloud Practitioner coursework).”

Bassam Amrou

Screened

Director-level Digital Solutions & IT Transformation Leader specializing in enterprise innovation

Plano, TX12y exp

“Entrepreneurial operator with experience creating business plans and securing venture capital to accelerate a go-to-market strategy. Demonstrates a structured approach to new ventures: framing opportunities, validating/de-risking via market/competitive/external analysis and financial modeling, then building governance, sponsorship, and an execution plan with the right team.”

“CTO candidate with experience in multiple VC-backed startups, emphasizing timing and disciplined scaling of engineering orgs (people, product, process). Evaluates technology choices through a customer-value lens and proactively flags business/tech misalignment, with a pragmatic approach to venture viability using TAM, competitive landscape, and leading indicators.”

Aidan Anderson

Screened

Director-level engineering leader specializing in AI, security, and FinTech SaaS

California, USA12y exp

“Engineer and bootstrap founder who has worked across roughly five venture-backed startups from pre-seed through Series E. He combines hands-on startup execution with strong judgment around product-market fit, founder fit, and customer validation, while independently building profitable, self-owned micro SaaS ventures on the side.”

“Software engineer working on an e-commerce platform, currently building a RAG-based recommendation system with a team new to the technology. Has delivered an end-to-end React/TypeScript website for a local car dealer and built an internal "encryption as a service" tool to secure sensitive data across repositories and through release/UAT, with experience debugging microservices integration issues.”

“AI/ML engineer with production experience building LLM-powered document intelligence and customer support systems in healthcare/insurance, emphasizing high-accuracy RAG, long-document processing, and robust monitoring/fallback mechanisms. Also automates and scales ML lifecycle workflows using Apache Airflow and Kubeflow, and partners closely with non-technical operations stakeholders to drive adoption.”

“Red Hat ML/LLM engineer who designed and deployed a production LLM-powered customer support automation system using RAG, improving latency by 30% via PEFT and vector search optimization. Built security and governance into retrieval (access-level filtering, encrypted Pinecone/ChromaDB) and delivered SHAP-based explainability via a dashboard for non-technical stakeholders. Experienced orchestrating distributed ML/RAG pipelines across AWS SageMaker and OpenShift with Airflow/Prefect, plus multi-agent workflows using CrewAI and LangGraph.”

Edward Robinson-Adams

Screened

Executive cybersecurity and AI leader, CEO/co-founder specializing in enterprise SaaS and strategy

Boston, MA35y exp

“Operator who took a seed-funded university spin-off in cybersecurity from zero revenue and heavy losses to profitability and industry leadership, while building the full internal ops stack (HR/payroll/benefits/401k) and the initial GTM engine (Salesforce/HubSpot, SPIN + MEDPICC). Personally led fundraising across 30+ VC pitches, raising $11.2M total and delivering $98M returned to investors to date, with additional upside from a subsequent spin-off.”

“Software engineer with experience building internal tools and admin consoles, including a stealth startup database management console and a Fidelity internship project that transformed QA test coverage tracking from unwieldy Excel sheets into a clearer, more actionable UI. Strongest signals are end-to-end ownership, modular app design, and practical iteration based on user feedback.”

“5-year .NET full stack developer who has applied AI-assisted development in an enterprise Cisco environment, using tools like GitHub Copilot and ChatGPT to accelerate microservice API delivery while maintaining architecture, security, and code quality standards. Notably reports a roughly 30% reduction in development time on a customer policy management/claims processing project through disciplined use of AI for boilerplate, testing, and design validation.”

“Founding engineer who has built web products end-to-end in startup settings, spanning FastAPI/React application development, auth, cloud deployment, and Kubernetes-based scaling. Particularly notable for designing custom GPU autoscaling for an AI-style recommendation product and later shipping workflow-driven healthcare support tooling using Temporal, Postgres, and modular backend logic.”

“Interned at Zonda where he built an AI-driven semantic search solution over ~280M housing/builder records. Iterated from local LLMs via llama.cpp quantization to a vector-embedding retrieval system, then boosted semantic accuracy with a custom spaCy NER layer and re-ranking, optimizing for latency through precomputation. Collaborated with economics-focused stakeholders to reduce manual document/paperwork time by enabling natural-language search over internal data.”