Staff Software Engineer (AI/ML)
Kaseya
About Kaseya
Kaseya is the leading provider of AI-powered IT management and cybersecurity software, serving Managed Service Providers (MSPs) and internal IT organizations worldwide. Our comprehensive platform helps organizations efficiently manage, secure, and automate their IT environments, driving operational efficiency and long-term business success.
Backed by Insight Partners, a leading global software investor, Kaseya has experienced sustained double-digit growth and continues to expand its global footprint. Today, Kaseya supports customers in more than 20 countries and manages over 15 million endpoints worldwide.
Founded in 2000, Kaseya has built a culture centered around innovation, accountability, and results. We are a high-growth, high-performance organization that values individuals who are driven, adaptable, and committed to delivering exceptional outcomes for our customers and teammates alike.
At Kaseya, success comes from embracing challenges, moving with urgency, and continuously raising the bar.
Position Summary:
- Kaseya is looking for an AI/ML Engineer to help build the intelligence layer of the Kaseya Intelligence Platform (KIP), an agentic AI runtime designed to autonomously manage IT operations for Managed Service Providers (MSPs). This is a hands-on engineering role at the intersection of Applied ML, LLMs, agentic AI, anomaly detection, and distributed systems.
- Build and iterate on agentic AI workloads that orchestrate vendor API calls, interpret PSA/RMM signals, and make autonomous decisions across MSP client environments
- Develop behavioral anomaly detection models that baseline per-workflow-identity call patterns, credential checkout volumes, and cross-vendor sequences: and flag deviations in real time
- Implement agentic-specific detection signals: tool call sequence anomalies, scope escalation attempts, decision branching inconsistencies, and output volume outliers
- Build harnesses and evaluation frameworks using tools like Amazon Bedrock, LangChain, and LangFuse to assess model quality, latency, and safety
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