AI Engineer

AppZen is the leader in autonomous spend-to-pay software. Its patented artificial intelligence accurately and efficiently processes information from thousands of data sources so that organizations can better understand enterprise spend at scale to make smarter business decisions. It seamlessly integrates with existing accounts payable, expense, and card workflows to read, understand, and make real-time decisions based on your unique spend profile, leading to faster processing times and fewer instances of fraud or wasteful spend. Global enterprises, including one-third of the Fortune 500, use AppZen’s invoice, expense, and card transaction solutions to replace manual finance processes and accelerate the speed and agility of their businesses.

 

At AppZen, we value candidates who are actively using AI tools to enhance productivity, automate repetitive tasks, and solve problems more efficiently. Across all roles, we are looking for team members who leverage AI in meaningful ways to drive impact in their work.

 

To learn more, visit us at www.appzen.com.

We are looking for an AI Engineer to help build and scale our next-generation AI platform, with a strong focus on agentic systems. In this role, you’ll design and develop intelligent agents powered by LLMs—leveraging tool calling, orchestration frameworks, and advanced context management to enable reasoning, planning, and autonomous decision-making across complex workflows. You’ll work hands-on with modern agentic stacks (e.g., LangGraph, Autogen), asynchronous and streaming architectures, and production-grade observability to bring scalable, real-world AI systems to life. If you’re passionate about pushing the boundaries of agentic AI and building systems that operate reliably in production, AppZen offers a high-impact environment to do just that.

We are looking for an AI Engineer to help build and scale our next-generation AI platform, with a strong focus on agentic systems. In this role, you’ll design and develop intelligent agents powered by LLMs—leveraging tool calling, orchestration frameworks, and advanced context management to enable reasoning, planning, and autonomous decision-making across complex workflows. You’ll work hands-on with modern agentic stacks (e.g., LangGraph, Autogen), asynchronous and streaming architectures, and production-grade observability to bring scalable, real-world AI systems to life. If you’re passionate about pushing the boundaries of agentic AI and building systems that operate reliably in production, AppZen offers a high-impact environment to do just that.

We are an equal opportunity employer and value diversity. All employment is decided on the basis of qualifications, merit and business need.

 

You can find our Privacy Notice linked on the bottom of our appzen.com website.

Experience working on Agentic systems using LLMs, tool calling, model context protocol, tracing observability tools.

Familiarity with Agent orchestration frameworks such as LangGraph, Autogen, or others.

Must be a power user of Agentic coding tools like Claude Code, Cursor, Codex.

Deep understanding of working on asynchronous and streaming system architectures for chat bots and asynchronous agents. Familiarity with tools such as Temporal, and either Python or GO programming languages.

Solid understanding of machine learning fundamentals, and familiar with standard algorithms and techniques

Ability to analyze a wide variety of data: structured and unstructured, observational and experimental, to drive system designs and product implementations 

Ensure data quality throughout all stages of acquisition and processing, including such areas as data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc. 

Manage your own process: identify and execute on high impact projects, triage external requests, and make sure you bring projects to conclusion in time for the results to be useful

Excellent written and verbal technical communication skills; communicate proposals and results in a clear manner backed by data and coupled with actionable conclusions to drive business decisions

BS/MS or equivalent experience in Computer Science, Engineering, Machine Learning, or other relevant technical field

Must have 5+ years of industry experience

Familiarity with data engineering concepts like data warehouses, streaming data. Specifics like Redshift or Spark are needed.

Infrastructure engineering and/or devops knowledge on systems such as Kubernetes, AWS.