Vetted Java Professionals

“Built and deployed a production LLM-powered document Q&A system using a strict RAG pipeline (LangChain-style orchestration + FAISS) to help users query large internal document sets. Demonstrates strong reliability focus through hallucination mitigation, curated offline evaluation with grounding checks, and production monitoring (latency/fallback rates) plus stakeholder alignment via demos and business metrics.”

Jack Oakley

Screened ReferencesStrong rec.

Director-level VR Game Programmer specializing in Unity and QA leadership

Austin, TX15y exp

“Unity/VR gameplay engineer who has shipped full games and built a robust coin economy + massive gear customization system (over a million combinations) backed by a cloud service. Notably discovered and fixed a severe backend security flaw by adding proper authentication (security key + OAuth2), and has hands-on VR performance optimization experience (OVR Metrics, LOD/mipmaps, imposters) plus multiplayer sports sync design using Photon PUN2.”

Kruti Mehta

Screened ReferencesStrong rec.

Mid-level Software Engineer specializing in backend systems and FinTech analytics

Maryland, USA5y exp

“Engineer with a pragmatic, high-leverage approach to AI-assisted development: uses AI and multi-agent workflows aggressively for implementation and internal tooling, while maintaining strict human oversight for user-facing features. Stands out for treating agents like junior engineers, breaking work into actionable tasks, and combining robust testing, local E2E validation, and feature-flag rollouts to safely ship production code.”

“Built and deployed an LLM-powered clinical decision support and risk monitoring platform for mental health at Valuai.io, emphasizing low-latency, evidence-grounded responses and crisis-safe behavior with clinician escalation. Strong production agent-orchestration background (LangChain/CrewAI) plus rigorous evaluation (clinician-in-the-loop + evaluator agent) and large-scale synthetic testing; also applied multi-agent workflows to document verification and fraud detection during an AI internship at Nixacom.”

“Built and deployed LLM-powered features for a startup organizational management application, focusing on real-world deployment constraints like latency and cost. Implemented RAG with FAISS and improved retrieval quality by switching embedding models (OpenAI/Hugging Face) and fine-tuning embeddings on medical corpora for a medical-report UI feature. Uses LangChain and LangGraph to orchestrate multi-node LLM API workflows and evaluates systems with metrics like latency, cost per request, and error taxonomy.”

“IT Analyst/research background with hands-on experience deploying and hardening a multi-agent AI support/triage system (ticket ingestion + knowledge-base retrieval) with strong emphasis on reliability and observability. Has debugged real production issues spanning backend services and network latency (sync failures/partial writes) and is comfortable in Linux environments; also has academic exposure to robotics simulation and ROS2.”

Iangolana Riantsoa RAMELSON

Screened ReferencesStrong rec.

Mid-level Full-Stack JavaScript Developer specializing in React, Next.js, and TypeScript

Madagascar, Madagascar5y exp

“Frontend engineer who led end-to-end delivery and scaling of an internal HR product (Easy Time), owning architecture decisions (React/TypeScript, Redux Toolkit, Tailwind/shadcn). Experienced building complex dashboard UIs with advanced filters and real-time interactions, collaborating directly with design (Figma) and shipping quickly via incremental delivery and GitLab CI-driven deployments.”

“ML/NLP practitioner who has delivered production systems in regulated domains, including a healthcare compliance pipeline using RAG (GPT-4/Claude) plus TF-IDF retrieval that increased document review throughput 4.5x. Also has hands-on experience improving fraud detection data quality via entity resolution (Levenshtein, Dedupe.py) validated with A/B testing, and building scalable, monitored workflows with Airflow, CI/CD, and AWS SageMaker.”