Applied AI Engineer

Zello

Applied AI Engineer building and operating production AI agents for Zello’s push-to-talk communication platform. Integrating LLMs with Slack, Jira, HubSpot, and Snowflake.

Posted 8/5/2026full-timeAustin • Texas • 🇺🇸 United StatesJuniorMid-LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining AI agents and automations, with a strong focus on production Python coding and integration of LLM APIs. Capable of managing operational health and collaborating effectively with both technical and non-technical stakeholders.

Highest-signal resume keywords

Production Python ExperienceLLM API IntegrationAPI System IntegrationOperational Ownership of AI SystemsQuality Monitoring and Testing

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonLLM APIsAPI IntegrationQuality MonitoringTest WritingAutomation DevelopmentDocumentationComponent DesignFeedback Loop ManagementRegression Detection

Soft Skills

CollaborationCommunicationProblem DecompositionAdaptability

Tools & Technologies

SlackJiraHubSpotSnowflake

Industry Keywords

AI EngineeringSoftware EngineeringAutomationIntegrationOperational Health

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Build AI agents and automations end-to-end, from scoping through deployment and ongoing maintenance
Write production Python code integrating LLM APIs into real workflows
Connect AI tools with Slack, Jira, HubSpot, and Snowflake through APIs
Monitor deployed agents, track quality metrics, triage failures, and ship improvements
Manage human reinforcement operations, including reviewing outputs and maintaining feedback loops
Build and maintain evaluation harnesses for regression detection and programmatic quality measurement
Create reusable components, patterns, and documentation for future development
Communicate with technical and non-technical stakeholders about deliverables, performance, and issues
Independently scope and ship AI tools for new use cases
Own ongoing health and operations of deployed AI agents

Requirements

What you’ll need

2–5 years of professional experience in software engineering, AI engineering, or a related technical role
Production Python experience with shipped tools, integrations, automations, or products
Practical understanding of LLM APIs, including prompt construction, context-window management, token economics, and tool-use patterns
Experience decomposing complex problems into components with well-defined interfaces
Experience integrating systems via APIs, including authentication, rate limits, documentation, and edge cases
Experience writing tests and building monitoring for quality and reliability
Comfort with operational ownership of deployed AI systems
Ability to learn new frameworks, APIs, and domains quickly
Clean, documented, maintainable code
Ability to collaborate with technical and non-technical stakeholders
Must be eligible to work in the United States

Benefits

Comp & perks

Competitive pay
Equity with significant upside
Healthy and well-balanced employee benefits
Flexible schedules
Time off
Sabbatical after every five years of service
Ping-pong table
Free snacks in the break room