Senior Software Engineer

Responsibilities

• Build web applications, APIs, data models, and backend services for AI research workflows.
• Build tools to author and manage evaluation tasks, rubrics, graders, suites, and rollout configurations, including workflows for publishing, versioning, auditing, and sharing research artifacts.
• Automate evaluation runs and generate useful reports for design, research, and engineering teams.
• Support synthetic data generation workflows for multimodal and conversational research, including tools that combine transcripts, media, and model comparisons.
• Translate product and research questions into measurable scenarios, automated graders, and human-evaluation campaigns, and develop measures of task quality, coverage, diversity, and semantic spread.
• Diagnose issues across application code, workers, model endpoints, deployments, and compute infrastructure, and improve reliability through health checks, observability, reproducible launch paths, data integrity safeguards, and automated verification.
• Lead migrations and dependent changes across research tools, evaluation systems, and supporting services.
• Partner closely with designers, model researchers, research engineers, and infrastructure teams, and onboard contributors to create high-quality evaluation and synthetic-data workflows.

Requirements

• 7+ years of professional software engineering experience.
• Strong full-stack experience across web applications, backend services, APIs, and data models, including ownership of complex systems spanning multiple services or repositories.
• Expertise in generative AI, multimodal models, or model-evaluation systems.
• Experience building effective internal tools for both technical and non-technical users.
• Comfortable debugging distributed workflows and production infrastructure.
• Strong product judgment and ability to translate ambiguous requirements into concrete plans.
• Energized by working between designers and researchers in a multidisciplinary team, connecting qualitative judgment to rigorous evidence.
• Clear communication and effective collaboration across engineering, design, and research.

Nice to Have

• Expertise in synthetic data generation, simulation, conversational AI, speech, video, motion, or embodied interaction.
• Experience with automated graders, human evaluation, supervised fine-tuning, reinforcement learning, or experiment- and dataset-management platforms.
• Operated GPU-backed inference or rollout workloads at very large scale.