Senior AI Platform Engineer

FactualIQ is building an enterprise AI platform that powers its Decision Engine and multi-agent systems for enterprise clients. The Senior AI Platform Engineer will architect scalable platform infrastructure, establish technical standards, and build reliable distributed systems for AI workflows, including orchestration, observability, security, evaluation, and resource optimization.

Responsibilities:

• Architect and implement highly scalable multi-agent orchestration platforms that handle thousands of concurrent agent executions with sub-second latency requirements
• Design advanced state management systems for distributed agent coordination, including checkpoint/recovery mechanisms, distributed locking strategies, and event sourcing architectures for full workflow reproducibility
• Build sophisticated configuration management systems that enable declarative workflow definitions with versioning, A/B testing capabilities, canary deployments, and automatic rollback mechanisms
• Architect and implement scalable security models for data and workflow protection, access control and service infrastructure security
• Design and implement advanced observability platforms specifically for AI workflows, including distributed tracing across agent boundaries, custom metrics for LLM performance, cost attribution systems, and automated anomaly detection
• Create sophisticated evaluation frameworks that combine multiple validation strategies (rule-based, statistical, LLM-as-judge) with automatic performance regression detection and workflow reliability scoring
• Build intelligent resource optimization systems including predictive scaling for agent workloads, intelligent request routing based on model capabilities, and cost-aware execution planning for LLM inference
• Design fault-tolerant integration patterns for external services, including circuit breakers, intelligent retry mechanisms with exponential backoff, and graceful degradation strategies when downstream services fail
• Architect data pipeline infrastructure for agent context management, including vector database optimization, semantic caching layers, and efficient state hydration for long-running workflows
• Actively manage, or participate in managing, product roadmaps, sprint design and progression, development pacing and quality markers for own work
• Develop and use effective technical documentation patterns for architecture and design activities, and continuously incorporate emerging best practices
• Research and implement best practices for both technical and process improvements, and advocate for broad adoption by communicating and illustrating their value