About this Staff Software Engineer (AI/ML) role at Kaseya Careers
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 was built by builders - and we're still building. We look for people who create rather than wait, who see a hard problem and lean in, and who treat challenges as raw material. At Kaseya, everyone plays a role in shaping the future of IT: whether you're in engineering, product, sales, marketing, customer support, or operations, your work helps protect, defend, and optimize IT environments across the globe.
We're building teams that grow, perform, and make an impact. If you're driven by the itch to make things better - a product, a process, a career - you'll fit right in.
At Kaseya, we don't just raise the bar. We build it.
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
- Read and translate research papers into production implementations: this role requires comfort navigating ML literature and turning concepts into working systems
- Contribute to connector codegen pipelines: agentic coding against vendor OpenAPI specs to accelerate Safe Connector Layer coverage across 40+ MSP tool APIs
- Work with the Temporal durable execution runtime to ensure agentic workloads behave predictably under failure, retry, and partial execution conditions
Required Qualification:
- Strong Programming/engineering skills; experience with LLM orchestration frameworks (LangChain, LlamaIndex, or similar)
- Hands-on experience with at least one major model provider (Bedrock, OpenAI, Vertex AI)
- Ability to read ML/systems research papers and extract implementable patterns
- Experience building evaluation harnesses, test suites, or benchmark pipelines for model or agent behavior
- Familiarity with behavioral anomaly detection, time-series analysis, or statistical baselining is a strong plus
- Experience with event-driven architectures (Kafka or similar) preferred
- Comfort working in a distributed, async-first team across multiple time zones
Preferred Qualification:
- Prior work in workflow automation, or enterprise security tooling
- Experience with ClickHouse or other columnar stores for analytics workloads
- Familiarity with Temporal or other durable workflow engines
Additional information
Kaseya provides equal employment opportunity to all employees and applicants without regard to race, religion, age, ancestry, gender, sex, sexual orientation, national origin, citizenship status, physical or mental disability, veteran status, marital status, or any other characteristic protected by applicable law.
