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Vetted Multi-Agent Systems Professionals
Pre-screened and vetted.
Mary Kotch
Executive CIO/CTO/CISO specializing in cloud, AI/ML, and cybersecurity transformation
“Fractional CTO and AI/ML consultant at Clover Health with deep insurance domain experience (15 years as CTO/CISO/AI). Has spent significant time in PE/VC-backed environments (including Aquiline Capital Partners and Apollo Group), designing and engineering platforms while delivering against budgets, audits, and regulatory compliance. Recently helped build an insurance startup (2020–2025) and is now seeking a full-time role at a startup.”
Chinedu Enwere
Mid Software Engineer specializing in distributed backend systems
“Engineering candidate deeply embedded in AI-native development, currently using tools like Cursor and Claude Code to generate most of their code and building internal agents for on-call monitoring, anomaly detection, and automated incident mitigation. Particularly interesting for teams exploring AI-first engineering workflows, multi-agent development setups, and operational automation at scale.”
Yishi Wang
Junior Machine Learning & Data Science professional specializing in LLMs and analytics
“Amazon internship experience building production GenAI analytics for the returns organization: a multi-agent LLM+RAG system that let analysts query multiple heterogeneous data sources in natural language without hand-written SQL. Also built and operationalized four Apache Airflow DAGs for large-scale ETL, emphasizing observability and freshness-aware metadata to keep outputs accurate and up to date.”
Director-level Engineering Leader specializing in distributed systems, cloud platforms, and developer APIs
Sumer Joshi
Senior Full-Stack Engineer specializing in backend systems and AI applications
“Candidate is deeply focused on AI-native software development, using a deliberate planner/implementer agent workflow with tools like Cursor, Claude, and Kimi. They also built a personal project called Config Proctor, an AI-agent-driven Terraform/AWS self-healing system that identifies infrastructure configuration gaps and proposes fixes.”
Christopher Bun
Executive AI/ML technology leader specializing in healthcare, biotech, and legal AI
“Repeat founder and startup advisor with experience spanning academic, health tech, legal tech, sports, and gaming. Has participated in fundraising and due diligence and has built companies, engineering teams, and software platforms from scratch, with a strong product-design-first approach to product-market fit and market selection.”
Yuxin Xiong
Intern Machine Learning Engineer specializing in LLM reasoning, agents, and deployment
“AWS AI Lab engineer who deployed a production Chain-of-Thought analytical agent for tabular reasoning, emphasizing grounded tool-constrained workflows with schema-validated intermediate outputs. Built robust evaluation/logging with step-level observability to catch regressions across model versions, and has experience scaling distributed LLM training via Slurm + DeepSpeed/FSDP with checkpointing and failure recovery.”
Avinash K
Mid-level Software Engineer specializing in AI/LLM and distributed systems
“Recent internship project at Google Workspace building an LLM-driven Python backend pipeline to extract/enrich NLP features from messy customer web domains and integrate them into a Domain Feature Store for personalization and promotions. Also has hands-on Kubernetes/Docker deployment experience for a Digital Signage SaaS backend with GitHub Actions CI, plus strong streaming-systems knowledge (Kafka exactly-once, schema evolution, Flink scaling) and built an information retrieval system handling 30,000+ cases.”
Dexin Huang
Junior AI Engineer specializing in LLM systems, RAG, and full-stack automation
“Built and deployed an AI receptionist product for field-service businesses (HVAC/electrician), including real-time Jobber scheduling integrations and Twilio-based calling. Combines hands-on customer/operator shadowing with strong production engineering (queueing to handle API limits, rigorous testing/mocking, mirrored prod environment) and cross-layer troubleshooting, driving user adoption through review/override workflows.”
jiawei Li
Intern Applied Scientist specializing in LLM agents for software engineering
“Applied Scientist intern at Amazon who built a production-adopted LLM-judge to evaluate an agentic chatbot’s intermediate reasoning and tool calls using a knowledge-graph grounding approach. Also published award-winning work (ACM SIGSOFT Distinguished Paper) using LangChain + GPT-4 tools to generate factually grounded commit messages, with rigorous human-centered evaluation metrics.”
Sai Gundeti
Mid-Level Backend Software Engineer specializing in distributed systems and billing platforms
“Full-stack engineer with Uber experience building finance/billing reconciliation systems: shipped and owned an internal operations dashboard (Next.js App Router/TypeScript) that cut investigation time from hours to minutes and improved load time from ~6–7s to <2s. Deep in Postgres modeling and performance (sub-200ms optimized queries) plus durable event-driven workflow orchestration with idempotency, retries/backoff, DLQs, and reconciliation jobs; also has seed-to-Series C startup experience emphasizing end-to-end ownership.”
Mid-Level Full-Stack Software Engineer specializing in FinTech and cloud-native AI systems
Mid-level AI/ML Engineer specializing in LLMs, RAG, and multi-agent systems
Senior Software Engineer specializing in AI/ML evaluation and full-stack systems
Senior Customer Success & Technical Account Leader specializing in AI/ML infrastructure
Junior AI Software Engineer specializing in LLM systems and retrieval (RAG)
Vigynesh Bhatt
Mid-level Software Engineer specializing in backend, cloud, and ML systems
“Software engineer with experience across Goldman Sachs, BYU Broadcasting, Juniper Networks, and an edtech startup (Doubtnut), spanning data migrations, AWS-based media backends, and microservices observability. Built a Redis/ElastiCache caching layer in front of DynamoDB/S3 to improve media delivery latency and cost, and created an SEO indexing automation tool using the Google Search Console API that saved ~15–30 person-hours per day.”
David Proctor
Executive Enterprise Architecture & AI Strategy Leader specializing in modernization and agentic AI platforms
“Technically and operationally oriented builder with startup ideas of their own, including an AI services firm in the ideation stage. Stands out for a practical understanding of venture studios and accelerators, with fluency in founder-market fit, MVP validation, hiring, and investor readiness, and a measured approach to going all-in only on high-signal opportunities.”
Osvaldo Calles
Senior Software Engineer specializing in developer tools, cloud automation, and generative AI
“Built and deployed a production chatbot on osvaldocalles.com and iterated through real-world LLM engineering issues: model quota/cost tradeoffs (migrating to Nova Pro), RAG accuracy via semantic chunking, AWS IAM/guardrail/security pitfalls, and Lambda/API Gateway streaming constraints (prefers JS for streaming layer). Experienced with agent orchestration using Strands SDK (AWS-focused) and LangGraph (Vercel/container deployments), plus evaluation pipelines using LLM-as-evaluator, dashboards, and staged model rollouts.”