Forward Deployed Engineer

Build production-grade AI systems alongside leading AI labs and enterprise teams. As a Forward Deployed Engineer, you will combine applied AI research, ML infrastructure, data intelligence, and partner-facing engineering to turn ambiguous opportunities into reliable multi-turn agent workflows.

You will work directly with strategic partners as a technical research and implementation partner, helping define research direction, curate high-quality data, implement machine learning and evaluation pipelines, and develop agentic systems for production use. This role requires comfort moving between research questions, technical architecture, hands-on engineering, and partner execution.

• Collaborate with AI labs and enterprise partners to define research goals, technical requirements, and project direction.
• Build data intelligence systems to collect, organize, evaluate, and improve training and evaluation data at scale.
• Implement ML pipelines for data curation, model training, evaluation, experimentation, and continuous improvement.
• Design data taxonomies, labeling systems, and quality frameworks that strengthen 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.
• Translate ambiguous AI challenges with research and engineering teams into scoped technical projects and production systems.
• Develop infrastructure for model inference, experimentation, evaluation, and deployment across frontier AI platforms.
• Create systems that move partners from one-off AI experiments to reliable, repeatable, multi-turn agent workflows.
• Own the full system lifecycle, including discovery, architecture, implementation, deployment, reliability, iteration, and partner success.

• Ability to operate independently in ambiguous, partner-facing environments with strong technical and product ownership.
• Strong Python engineering experience and a record of building and shipping production systems end to end.
• Experience with LLMs, agentic systems, multi-turn workflows, tool use, RAG, or AI automation.
• Experience building or maintaining data pipelines, ML infrastructure, evaluation systems, or research workflows.
• Strong understanding of data quality, taxonomy design, labeling workflows, and AI dataset curation.
• Comfort working directly with technical partners, researchers, founders, and enterprise stakeholders.

• Experience 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 serving as a technical partner to external customers, research teams, or strategic enterprise accounts.

• Full-time role.
• Remote work with travel required.

Annual compensation range: $300, 000 to $650, 000.