Senior Software Engineer (Agent Oversight)

Join the Applied Intelligence Systems team at Scale, a fast-growing company focused on pushing the boundaries of agentic applications in various enterprise and government use cases. As a Senior Software Engineer on Agent Oversight, you will build the platform infrastructure that allows for the observation, evaluation, and improvement of production agents at scale. You will work closely with ML engineers, own your systems end-to-end, and ensure rigorous technical standards are maintained.

• Concevoir et construire des capacités de plateforme essentielles pour le déploiement, la surveillance et l'évaluation des applications agentiques en production.
• Construire des API fiables et des pipelines de données qui capturent la télémétrie des agents, les signaux d'évaluation et les métriques de performance à grande échelle.
• Travailler en étroite collaboration avec les ingénieurs ML pour transformer les prototypes, les boucles d'évaluation ou les flux de travail d'amélioration des modèles en capacités de plateforme fiables.
• Track record of taking ownership of features or components end-to-end — from design through production — within a larger platform or system
• Gives direct, substantive feedback on designs and code, and takes it the same way — and mentors others as they grow
• Strong problem-solving skills and the ability to work independently or as part of a tight-knit, cross-functional team
• Comfortable operating in an ambiguous, fast-changing domain where tooling and best practices are still being defined
• Working knowledge of how LLM or ML systems behave in production: evaluation signals, failure modes, prompt/tool-calling workflows, experiment results, data quality issues, and the tradeoffs between offline evals and live customer behavior
• Experience building infrastructure or platforms that other engineering teams build on top of (internal platform, developer tools, or similar)
• 4+ years of professional software engineering experience, with strong fundamentals in backend/distributed systems, APIs, and data pipeline design
• Experience partnering closely with ML engineers or applied researchers to turn prototypes, eval loops, or model-improvement workflows into reliable platform capabilities, without needing to own model training, modeling strategy, or research direction
• Hands-on experience building production software for ML/LLM-powered products or platforms, such as evaluation systems, observability/monitoring, experimentation infrastructure, agent runtimes, model-serving-adjacent services, or telemetry/data pipelines
• Excited to work directly with ML engineers and customer-facing teams, including challenging assumptions in designs and metrics when platform behavior, model behavior, and customer needs intersect
• Deep experience building or maintaining observability, monitoring, or evaluation systems for ML/LLM-powered products in production
• Familiarity with agent architectures — tool use, planning, multi-agent orchestration
• Exposure to MLOps, feature stores, model serving, or experiment infrastructure
• Experience working in regulated or enterprise contexts
• Experience reviewing others’ technical designs or mentoring engineers at a senior/staff level