Forward Deployed Engineer | Full-time - Remote
# Forward Deployed Engineer | Full-time - Remote **Xperteez Technology** · United States · `Remote` · `Full Time` 💼 **Уровень роли:** `Mid-level` 🕒 **Статус:** *Опубликовано: сегодня* · *Источник: Himalayas (JSON API)* --- ### Top Skills & Match 🎯 **Ключевой стек роли:** `[Forward-Deployed-Engineer]` `[Machine-Learning-Engineer]` `[AI-Engineer]` `[Software-Engineer]` `[Data-Engineer]` `[Remote-Forward-Deployed-Engineer]` `[Mid-Level-Forward-Deployed-Engineer]` `[Forward-Deploy-Engineer]` `[Forward-Deployment-Engineer]` --- ### About the Role Job Title: Forward Deployed Engineer Job Type: Full-time Location: Remote / Travel-required The Role We’re hiring a Forward Deployed Engineer to work directly with the world’s leading AI labs and enterprises as a technical research and implementation partner. This role sits at the intersection of applied AI, ML infrastructure, data intelligence, and partner-facing product development. You’ll help strategic partners define research directions, structure and curate high-quality data, implement ML and evaluation pipelines, and build the agentic systems that extend multi-turn agents and workflows in production. You should be comfortable moving between ambiguous research questions, technical architecture, hands-on engineering, and partner-facing execution. Required Skills - Python - LLM Systems - ML Infrastructure - RAG/AI Automation What You’ll Work On - Work directly with leading AI labs and enterprise partners to define research goals, technical requirements, and project direction. - Build large-scale data intelligence systems for collecting, organizing, evaluating, and improving training and evaluation data. - Implement ML pipelines for data curation, model training, evaluation, experimentation, and continuous improvement. - Design data taxonomies, labeling systems, and quality frameworks that improve dataset structure, model performance, and research outcomes. - Develop LLM applications, including multi-agent systems, tool-using agents, RAG workflows, evaluation harnesses, and human-in-the-loop systems. - Partner with research and engineering teams to translate ambiguous AI problems into scoped technical projects and production systems. - Develop infrastructure for model inference, experimentation, evaluation, and deployment across frontier AI platforms. - Build systems that help partners move from one-off AI experiments to reliable, repeatable, multi-turn agent workflows. - Own systems across the full lifecycle, including discovery, architecture, implementation, deployment, reliability, iteration, and partner success. What We're Looking For - Able to operate independently in ambiguous, partner-facing settings with strong technical and product ownership. - Strong Python engineer with experience building and shipping production systems end to end. - Experience working with LLMs, agentic systems, multi-turn workflows, tool use, RAG, or AI automation. - Built or maintained data pipelines, ML infrastructure, evaluation systems, or research workflows. - Strong understanding of data quality, taxonomy design, labeling workflows, and dataset curation for AI systems. - Comfortable working directly with technical partners, researchers, founders, and enterprise stakeholders. Preferred Qualifications - Background at a startup, AI infrastructure company, applied AI company, or research-focused engineering team. - Experience building systems for multi-turn agents, agent evaluation, workflow automation, or human-in-the-loop AI. - Experience designing data taxonomies, annotation systems, evaluation rubrics, or dataset quality pipelines. - Experience acting as a technical partner to external customers, research teams, or strategic enterprise accounts. - Familiarity with modern LLM tooling, agent frameworks, model evaluation stacks, and ML experimentation platforms. Originally posted on Himalayas
- Forward-Deployed-Engineer
- Machine-Learning-Engineer
- AI-Engineer
- Software-Engineer
- Data-Engineer
- Remote-Forward-Deployed-Engineer
- Mid-Level-Forward-Deployed-Engineer
- Forward-Deploy-Engineer
- Forward-Deployment-Engineer
Наблюдалась 2026-10-03, впервые 2026-10-03, источник — Himalayas (JSON API).