Staff Software Engineer (AI/ML)
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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 platform designed to autonomously manage IT operations for Managed Service Providers (MSPs).
- This is a hands-on engineering role at the intersection of Generative AI, agentic AI, applied machine learning, and distributed systems. You will build production-grade AI agents that orchestrate vendor API calls, interpret PSA/RMM signals, make autonomous decisions, and operate reliably across complex MSP environments.
- You will also develop AI/agent evaluation frameworks, behavioral anomaly detection, safety mechanisms, and production workflows, while translating relevant ML/AI research into practical implementations. The role requires strong software engineering fundamentals and the ability to take AI concepts from experimentation through production.
- 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:
- 5+ years of experience in AI/ML engineering, software engineering, applied machine learning, or a related field, with strong hands-on development experience.
- Proven experience building and deploying production-grade LLM or agentic AI applications, beyond basic LLM/API experimentation.
- Strong programming and software engineering skills, preferably with Python, along with experience building scalable and reliable production systems.
- Hands-on experience with LLM/agent orchestration frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent technologies.
- Practical experience with at least one major LLM/model platform, such as Amazon Bedrock, OpenAI, Google Vertex AI, or equivalent.
- Experience designing and implementing AI/LLM evaluation frameworks, including evaluation harnesses, benchmarks, test suites, quality measurement, latency analysis, or agent behavior evaluation.
- Strong understanding of agentic AI concepts, including tool/function calling, agent orchestration, multi-step workflows, decision-making, and autonomous execution.
- Ability to read and interpret ML/AI research papers and translate relevant techniques into working software or production implementations.
- Strong understanding of AI reliability and safety, including hallucination handling, guardrails, unexpected tool calls, behavioral anomalies, and evaluation of agent behavior.
Preferred Qualification:
- Experience building AI/ML systems for workflow automation, enterprise platforms, cybersecurity, security tooling, or IT operations.
- Experience with Temporal or other durable workflow/execution engines for reliable AI-agent execution.
- Experience with ClickHouse or other columnar/analytical databases for high-volume analytics and behavioral data.
- Experience building API/tool integrations, OpenAPI-based code generation, connector frameworks, or automated agent tool ecosystems.
- Experience with LLM observability, agent tracing, evaluation platforms, guardrails, and AI safety tooling, including tools such as LangFuse or equivalent.
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.
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