Forward Deployed Engineer

Forward Deployed Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Forward Deployed Engineer based in United States.

This role places you directly alongside leading AI labs and enterprise partners to turn complex AI challenges into scalable technical solutions. You'll operate at the intersection of applied AI, machine learning infrastructure, data intelligence, and product engineering. The position combines hands-on development with technical discovery, architecture, experimentation, and partner-facing collaboration. You'll build the data, ML, evaluation, and agentic systems that help organizations move advanced AI capabilities from experimentation into production. Working in a fast-moving and highly autonomous environment, you'll have ownership across the full lifecycle of projects, from initial discovery through deployment and iteration. This is an opportunity to contribute to cutting-edge AI initiatives while solving challenging problems alongside researchers, engineers, and technical leaders.

Accountabilities:

• Work directly with AI labs and enterprise partners to define research objectives, technical requirements, project scope, and implementation priorities.
• Translate ambiguous AI and research challenges into clearly scoped technical projects, architectures, and production-ready systems.
• Build scalable data intelligence systems for collecting, organizing, evaluating, and continuously improving training and evaluation datasets.
• Develop and maintain ML pipelines supporting data curation, model training, evaluation, experimentation, and continuous improvement.
• Design data taxonomies, labeling systems, annotation workflows, and quality frameworks that improve dataset consistency and model performance.
• Develop LLM-powered applications, including multi-agent systems, tool-using agents, multi-turn workflows, RAG applications, evaluation harnesses, and human-in-the-loop systems.
• Build infrastructure supporting model inference, experimentation, evaluation, deployment, and reliable operation across modern AI platforms.
• Help partners transition from one-off AI experiments to repeatable, scalable, and reliable agentic workflows.
• Collaborate closely with research and engineering teams to implement technical solutions aligned with partner objectives.
• Own projects across the complete lifecycle, including discovery, architecture, implementation, deployment, reliability, iteration, and partner success.
• Communicate technical concepts and project progress effectively with researchers, engineers, founders, and enterprise stakeholders.

Requirements

• Strong ability to work independently in ambiguous, fast-moving, and partner-facing environments while taking ownership of technical and product outcomes.
• Strong Python engineering skills with demonstrated experience building and shipping production systems end to end.
• Hands-on experience with LLMs, agentic systems, multi-turn workflows, tool use, RAG, or AI-powered automation.
• Experience building or maintaining data pipelines, ML infrastructure, evaluation systems, or research-oriented engineering workflows.
• Strong understanding of data quality, taxonomy design, labeling and annotation workflows, dataset curation, and AI evaluation practices.
• Ability to work directly with technical partners, researchers, founders, and enterprise stakeholders.
• Experience translating complex or ambiguous requirements into practical technical architectures and deliverable systems.
• Experience in a startup, AI infrastructure company, applied AI environment, or research-focused engineering team is preferred.
• Experience building multi-turn agent systems, agent evaluation frameworks, workflow automation, or human-in-the-loop AI solutions is preferred.
• Familiarity with modern LLM tooling, agent frameworks, model evaluation stacks, and ML experimentation platforms is preferred.
• Experience designing evaluation rubrics, annotation systems, data taxonomies, or dataset quality pipelines is a plus.
• Strong communication, collaboration, problem-solving, and technical ownership skills.

Benefits

• Base salary range of $180,000–$250,000 USD annually.
• Equity compensation eligibility for all employees.
• Potential performance-based bonuses depending on role and applicable policies.
• Comprehensive health benefits, including reimbursement of up to 100% of health-insurance premiums.
• Paid time off.
• 401(k) plan with company matching.
• Remote-first work environment designed to support flexibility and high-impact collaboration.
• Opportunity to work on advanced AI initiatives with leading research and enterprise organizations.
• Significant technical ownership across AI infrastructure, data systems, agentic applications, and production deployments.
• Exposure to cutting-edge LLM, ML, evaluation, and AI automation technologies.