Vetted AI Engineers

“Built and deployed a production LLM-powered clinical note summarization system used by care managers to speed review of 5–20 page unstructured medical records. Implemented safety-focused validation (prompt constraints, rule-based and section-level checks, human-in-the-loop) to reduce hallucinations while maintaining low latency and meeting privacy/regulatory constraints, integrating via APIs into existing clinical tools.”

“ML/LLM engineer at Charles Schwab who built a production loan-advisor chatbot integrated with internal knowledge and loan-calculator APIs, adding strict numeric validation to prevent rate hallucinations and optimizing context to control costs. Also runs ~40 Airflow DAGs orchestrating retraining/ETL/drift monitoring with an automated Snowflake→SageMaker→auto-deploy pipeline, and uses rigorous testing plus canary rollouts tied to business metrics and compliance constraints.”

Prateek Pravanjan

Screened

Junior Machine Learning Engineer specializing in LLM evaluation and GenAI pipelines

Remote1y exp

“LLM/agent engineer who built a production LangGraph multi-agent orchestrator connecting GitHub and APM/observability signals with a chain-of-verification loop for root-cause analysis. Emphasizes pragmatic architecture (start simple with state summaries), performance tuning (async LLM calls, Docker), and rigorous evaluation (LLM-as-judge, adversarial testing, hallucination/instruction adherence metrics, tool-call tracing) while iterating with non-technical stakeholders via A/B testing.”

Shweta Gupta

Screened

Senior Backend Software Engineer specializing in Java microservices, Kafka, and AWS

Seattle, WA6y exp

“AI engineer who shipped a production chat assistant for a storage company by building the underlying RAG-style knowledge base (document ingestion, chunking/embeddings, FAISS vector store) and an admin update interface to keep content current. Also has full-stack delivery experience (Python REST APIs + React/TypeScript UI) and AWS operations using Terraform/Jenkins, including handling a real production performance incident by optimizing DB queries and adding auto-scaling.”

Poorna Vishnu

Screened

Mid-level AI Engineer specializing in LLM workflows and agent-based systems

Texas City, TX4y exp

“LLM/agent workflow engineer with production experience at T-Mobile, focused on scalable agent architecture and robust real-time evaluation/monitoring pipelines. Partnered closely with marketing and product to automate customer engagement and other business workflows, translating AI capabilities into measurable KPI impact via dashboards and continuous performance tracking.”

“Full-stack engineer who built BrewAI, a cloud-native AI resume optimization platform on GCP using React, TypeScript, LangChain, and Gemini, with scalable async job processing and LLM safety guardrails. The product gained real-world traction when an undergraduate college in India asked students to use it for internship resume drafting, and the candidate also has team lead experience shipping an early-stage ERP system.”