Sr. AI Engineer

ZYLO, INC.-posted 2 days ago

Full-time • Mid Level

Indianapolis, IN

101-250 employees

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Zylo is the enterprise leader in SaaS Management, enabling companies to discover, manage, and optimize their SaaS applications. Zylo helps companies reduce costs and minimize risk by centralizing SaaS inventory, license, and renewal management. Trusted by industry leaders, Zylo’s AI-powered platform provides unmatched visibility into SaaS usage and spend. Powered by the industry’s most intelligent discovery engine, Zylo continuously uncovers hidden SaaS applications, giving companies greater control over their SaaS portfolio. With more than 30 million SaaS licenses and $34 billion in SaaS spend under management, Zylo delivers the deepest insights, backed by more data than any other provider. Overview We are seeking an experienced Senior AI Engineer to lead the evolution of our enterprise SaaS platform's agentic AI capabilities. You'll drive strategic AI initiatives that solve complex client problems while working with large-scale datasets for global enterprise customers. This role combines deep technical expertise in AI agents, RAG systems, and enterprise integration with strategic thinking about how AI can transform our platform and deliver exceptional business value..

Drive strategic AI initiatives that directly impact client success and business growth, defining technical roadmaps and influencing product strategy to solve complex enterprise problems
Architect and enhance our agentic processes for enterprise-scale deployments, building sophisticated multi-agent orchestration patterns for complex workflows
Design advanced agent memory systems and context management solutions that maintain coherence across long-running conversations and extended enterprise tasks
Build and implement RAG (Retrieval-Augmented Generation) systems to dramatically improve AI accuracy, including knowledge retrieval pipelines and semantic search optimization for large-scale datasets
Develop enterprise-grade MCP (Model Context Protocol) services enabling seamless client agent integration with standardized APIs, security protocols, and comprehensive documentation
Leverage AWS technologies (Bedrock, Lambda, etc) to architect AI solutions with optimal performance, cost efficiency, and enterprise-scale LLM integration
Design and optimize schemas for storing LLM interactions, agent state, and conversation history while building monitoring systems for AI operations
Lead cross-functional initiatives to integrate AI throughout our platform ecosystem, partnering with product and engineering teams to deliver measurable business value
Translate complex technical AI concepts into business value, working directly with enterprise clients to understand their needs and influence strategic platform decisions
Mentor engineering teams on AI best practices, emerging technologies, and enterprise AI governance while maintaining high engineering standards for production AI systems.

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
5+ years of experience in AI/ML engineering with at least 2 years in a senior role
Proven experience building and deploying AI agents or conversational AI systems in production
Experience working with large-scale enterprise datasets and SaaS platforms.
Expertise in design patterns for memory systems and context management solutions and optimization for AI workloads
Experience with Amazon Bedrock and AWS Lambda for serverless AI deployments
Experience with RAG systems, vector databases, and semantic search
Understanding of Model Context Protocol (MCP) and AI agent integration patterns
Proficiency in programming languages such as Python, PySpark, SQL and ML frameworks such as TensorFlow, PyTorch..
Knowledge of enterprise security patterns and compliance requirements
Ability to articulate technical concepts to technical and non-technical stakeholders.
Ability to thrive in a fast-paced, dynamic environment.
Flexibility to adapt to changing priorities and requirements.

Experience in SaaS Management or Software Asset Management.
Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or a related field.
Knowledge of ethical AI, bias mitigation, and AI safety best practices
Experience with LangChain and LangGraph frameworks

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