Staff AI Platform Engineer II

Enhanced Job Description

📍 Job Overview

• Job Title: Staff AI Platform Engineer II
• Company: Kaseya
• Location: United States - Remote
• Job Type: Full-Time
• Category: AI & Machine Learning
• Date Posted: 2025-08-01
• Experience Level: Mid-Level (5-10 years)
• Remote Status: Remote

🚀 Role Summary

Kaseya is seeking a dynamic Staff AI Platform Engineer II to join their team and build the intelligent core of their AI platform. This role involves engineering autonomous agents capable of perception, reasoning, and learning in complex environments. The ideal candidate will have a strong background in agentic architectures and applied machine learning, with a focus on building intelligent systems and autonomous agents.

💡 Primary Responsibilities

1. Agent Design & Implementation: Design and implement autonomous AI agents capable of perception, reasoning, and learning in complex, real-world environments.
2. Architecture Development: Develop and optimize agentic architectures using LLMs, vector databases, and symbolic reasoning engines.
3. Performance Optimization: Apply advanced RAG techniques, prompt engineering, and fine-tuning to enhance agent performance.
4. Knowledge Graph Integration: Integrate knowledge graphs and multi-modal capabilities to enable contextual and adaptive agent behavior.
5. Evaluation & Deployment: Build robust evaluation frameworks, A/B testing pipelines, and model versioning systems for agent deployment.
6. Collaboration & Improvement: Collaborate with platform, data, and product teams to ensure seamless deployment and continuous improvement of intelligent agents.

🔑 Skills & Qualifications

Education:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

Experience:

• 5-7+ years of experience in applied AI/ML, with a strong focus on building intelligent systems and autonomous agents.

Required Skills:

• Deep expertise in Python and/or TypeScript.
• Hands-on experience with multiple LLMs (e.g., GPT, Llama, Claude, Gemini), including fine-tuning, advanced RAG techniques, and prompt engineering.
• Proficiency with agent frameworks such as LangChain, LangGraph, AutoGen, or CrewAI.
• Background in model evaluation, A/B testing, and versioning for AI models.
• Familiarity with vector databases (e.g., Pinecone, Milvus, Chroma) and knowledge graphs (e.g., Neo4j, RDF).
• Understanding of multi-modal LLM capabilities and responsible AI practices.

Preferred Skills:

• Experience with causal inference and its application in agent decision-making.
• Familiarity with formal methods for agent behavior verification.
• Background in human-AI interaction design and UX for AI-powered applications.
• Experience developing agents for domains like cybersecurity or IT operations automation.
• Knowledge of neuro-symbolic AI and reinforcement learning from human feedback (RLHF) or direct preference optimization (DPO).

💼 Benefits & Compensation

• Salary: Competitive salary based on experience and location, with a range of $150,000 - $200,000 USD (estimated based on industry standards and regional cost of living).
• Benefits:
  • Comprehensive health, dental, and vision insurance.
  • 401(k) matching and employee stock purchase plan.
  • Flexible time off and remote work options.
  • Professional development opportunities and tuition reimbursement.
  • Employee referral bonuses and company equity.

📈 Work Environment

• Office Type: Remote (100% remote work).
• Work Schedule: Flexible hours with a focus on results and performance, not hours worked.

💡 Team & Culture

• Industry: IT infrastructure and security management solutions for Managed Service Providers (MSPs) and internal IT organizations worldwide, powered by AI.
• Company Size: Medium (200-999 employees).
• Founded: 2000.
• Team Structure: Cross-functional teams with a focus on collaboration and knowledge sharing.
• Development Methodology: Agile/Scrum methodologies and code review processes.
• Company Culture: BOLD, gritty, and accountable, with a focus on continuous learning and innovation.

💻 Application & Interview Process

1. Application: Submit your application through the provided link.
2. Technical Preparation: Brush up on your technical skills, focusing on AI/ML fundamentals, agent architecture, and system design.
3. Interview Process:
   • Technical Preparation: Prepare for technical questions on AI/ML fundamentals, agent architecture, and system design.
   • Technical Challenge: Expect a technical challenge focusing on agent planning, reasoning, and deployment.
   • Portfolio Presentation: Prepare a portfolio showcasing your AI/ML projects, agent implementations, and relevant case studies.
   • Behavioral & Cultural Fit: Demonstrate your cultural fit and alignment with Kaseya's values and work environment.

💡 Company & Location

• Company: Kaseya, a leading provider of complete IT infrastructure and security management solutions for MSPs and internal IT organizations worldwide, powered by AI.
• Location: United States - Remote (with a preference for applicants in the Eastern Time Zone).

📜 Equal Opportunity Statement

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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Content Guidelines (IMPORTANT: Do not include this in the output)

Web Technology-Specific Focus:

• Tailor every section specifically to AI & Machine Learning roles, with a focus on autonomous agent design, LLMs, and agentic architectures.
• Include relevant AI/ML keywords, agent planning techniques, and emerging technologies in the description.
• Emphasize the role's impact on AI-driven decision-making, user experience, and infrastructure management.

Quality Standards:

• Ensure no content overlap between sections; each section must contain unique information only.
• Use Enhancement Notes sparingly and only when making significant inferences about AI/ML role characteristics and company context.
• Be comprehensive yet concise, prioritizing actionable information over descriptive text.
• Maintain appropriate spacing between sections for visual clarity.

Industry Expertise:

• Include specific AI/ML technologies, frameworks, and tools relevant to the role, such as LLMs, agent frameworks, and vector databases.
• Address AI/ML career progression paths and technical leadership opportunities in AI teams.
• Provide tactical advice for AI portfolio development, live demonstrations, and project case studies.
• Include AI/ML-specific interview preparation and coding challenge guidance.

Role-Specific Insights:

• Highlight the role's focus on autonomous agent design, agentic architectures, and AI-driven decision-making.
• Emphasize the role's impact on AI-powered user experiences, infrastructure management, and emerging technologies.
• Provide detailed, company-specific context and tactical advice for AI technology professionals.

Actionable Depth:

• Provide specific, practical tips and detailed preparation advice for technical interviews, focusing on AI/ML fundamentals, agent architecture, and system design.
• Include specific, relevant keywords for AI/ML roles, organized by category: programming languages, AI/ML frameworks, tools, methodologies, soft skills, industry terms, etc.
• Tailor the output to the specific AI/ML role and company context, with a focus on web technology industry best practices and career progression patterns.

Professional Standards:

• Maintain consistent formatting, spacing, and professional tone throughout the output.
• Use AI/ML and agentic architecture terminology appropriately and accurately, with a focus on the specific AI/ML role and company context.
• Include comprehensive benefits and growth opportunities relevant to AI technology professionals.
• Provide actionable insights that give AI/ML candidates a competitive advantage in their career search and interview preparation.

Target Length:

• The enhanced job description should have a target length of 1,100-1,200 words to optimize user value and SEO performance.