Vetted Workflow Orchestration Professionals

“Built and shipped an end-to-end LLM agent during an AT&T internship to automate network troubleshooting, with production-style reliability safeguards (timeouts/retries/fallbacks) and structured, state-machine orchestration; project won 3rd place in AT&T’s nationwide intern innovation challenge and was demoed to leadership. Also handled messy multi-partner data at Tencent by implementing schema validation/normalization, confidence-threshold fallbacks, and idempotent Python/ORM-based pipelines.”

“Serverless-focused backend/data engineer who has delivered production Python services on AWS (FastAPI on Lambda/API Gateway) plus Glue-based ETL pipelines from S3 to relational databases. Strong in operational reliability (timeouts, retries, monitoring/alerts) and modernization work, including parallel-run parity validation for migrating legacy batch logic to Python services. Demonstrated measurable SQL tuning impact (15 min to under 3 min).”

“LLM/multimodal systems builder who developed DuetGen, a practical multimodal interleaved text-image generation system using a decoupled MLLM planner and video-pretrained diffusion transformer for high-quality image generation with step-wise alignment. Built a 298K-sample interleaved dataset across 8 domains/151 subtasks and deployed a GPT-5-based automated evaluation framework; also has LangChain-based multimodal agent orchestration experience with custom state management and reliability testing.”

“Built and shipped an LLM-powered data quality assistant that generates maintainable validation checks from metadata while executing validations via Great Expectations, exposed through FastAPI and integrated into Airflow-managed pipelines. Emphasizes production reliability (structured outputs, guardrails, monitoring, versioning, human review) and works closely with compliance/operations teams to deliver clear, auditable, user-friendly AI outputs.”

Abhinav Bandaru

Screened

Junior Data Scientist specializing in Generative AI and agentic LLM systems

San Jose, CA1y exp

“LLM/agentic-systems builder who has shipped production tools for investment research and procurement insights, including a company screener that processes thousands of conference-listed companies using FireCrawl + Google Search + Gemini. Demonstrates strong orchestration expertise (LangGraph multi-agent graphs), performance optimization (async/batching to sub-30s), and pragmatic reliability/evaluation practices with stakeholder-friendly UX (real-time cost tracking and model/parameter toggles).”

“Built and shipped a real-time AI phone agent for small businesses that handles bookings/FAQs/messages using streaming ASR, an LLM with tool-calling, and TTS; deployed to production for multiple paying customers. Demonstrates strong applied LLM reliability practices (tool-first grounding, retrieval, hard-negative testing, and production monitoring) and experience orchestrating multi-step AI workflows with Airflow, Prefect, and AWS Step Functions.”

“Frontend engineer from Amazon Advertising who owned a sophisticated React/TypeScript ad creative builder used by advertisers and ad ops teams. Stands out for combining deep browser-level debugging with product-minded UX improvements that reduced support escalations and made complex multi-placement ad configuration faster and more reliable for power users.”

“Entrepreneurial builder and former founding CTO of a Y Combinator startup that was acquired. Now in the planning stage for a new venture (considering edtech, media creation, and food/"intelligent servicing"), emphasizing early design partners, rapid testing, and iteration to validate ideas.”

Nikhila Nandgopal

Screened

Director-level product and strategy leader specializing in enterprise modernization and emerging tech

Chicago, IL5y exp

“Product leader with an unusual blend of investment banking, consulting, chief of staff, and agentic AI experience. At Kyndryl, they turned stalled mainframe modernization and seller-enablement efforts into quantified materials, staffing/delivery tools, and ~15 active POCs, while also bringing product and Agile discipline to ambiguous platform work.”

Yishi Wang

Screened

Junior Machine Learning & Data Science professional specializing in LLMs and analytics

Chicago, IL3y exp

“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.”