Senior AI Engineer

Zylo

Senior AI Engineer driving strategic AI initiatives and solutions for Zylo’s SaaS management platform, leveraging large-scale datasets and AWS technologies.

Posted 5/1/2026full-timeIndianapolis • 🇺🇸 United StatesSeniorWebsite

Tech Stack

Tools & technologies

AWSPySparkPythonPyTorchSQLTensorflow

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

Professional development opportunities
Work with large-scale datasets
Collaborate with cross-functional teams

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

AI engineeringML engineeringconversational AI systemsmemory systems designcontext management solutionsRAG systemsvector databasessemantic searchPythonTensorFlow

Soft Skills

strategic thinkingcross-functional collaborationmentoringcommunicationinfluencingproblem-solvingleadershipclient engagementtechnical translationhigh engineering standards