Vetted Go Professionals

“Full-stack AI engineer who has built and deployed multiple end-to-end LLM products, including an AI interview assistant, a multi-agent market research platform, and a policy document explainer. Particularly strong in productionizing agentic workflows, integrating tools like Whisper, Tavus, LiveKit, CrewAI, and LangGraph, and hardening messy real-world AI/document pipelines with validation, memory isolation, and fallback handling.”

Tejaswi devarapalli

Screened

Junior Software Engineer specializing in backend systems and AI infrastructure

Los Angeles, CA2y exp

“Built both a full-stack AWS file-processing pipeline and a production AI document Q&A system ('smart-doc'). Stands out for combining strong cloud engineering with practical LLM/RAG architecture, including hybrid retrieval, reranking, structured outputs, confidence-based retries, and production monitoring.”

“Early-career backend developer building an Arc Raiders game-data API end-to-end in Go on AWS with PostgreSQL, making their first real deployment and learning system design hands-on. Also built an AI resume and cover letter generator using Gemini and has experience debugging open-source code and managing PRs in a capstone team project.”

“Recent graduate who independently built scholar.ai from scratch in roughly two weeks, shipping a full multimodal ingestion, retrieval, and grounded Q&A system for students. Also created Anchor SDK, an open-source framework for runtime hallucination detection and recovery, showing unusually strong depth in production LLM systems, evals, and reliability for an early-career candidate.”

“Application security engineer/advisor with hands-on experience securing AWS-based, containerized services and embedding SAST/DAST/SCA and container scanning into GitHub/GitLab CI/CD. Drove measurable outcomes (50% faster vuln triage, 40% fewer misconfigs) and has deep operational troubleshooting experience in Kubernetes (agent failures due to CPU throttling/network policies), plus pragmatic strategies to reduce developer friction and handle API rate limits.”

“Backend/ML engineer with deep fintech and marketplace experience: built a real-time financial analytics + algorithmic trading platform (Python/Postgres/Kafka/Redis) and drove major DB performance wins (10x faster analytics; sub-10ms response consistency). Also shipped an end-to-end ML recruitment matching platform (scraping/ETL/modeling/Django deployment) with reported 92% matching accuracy, and emphasizes production reliability via monitoring, blue-green deploys, and robust workflow error handling.”