AI Automation Engineer

StockX

AI Automation Engineer at StockX, designing and building intelligent automation systems. Collaborating across teams to improve operational efficiency and reduce manual efforts.

Posted 7/17/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSenior💰 $140,000 - $160,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and deploying AI-powered automation solutions, with a strong focus on LLMs, machine learning models, and API integrations. Proven ability to build scalable workflows and ensure compliance with data privacy and security policies.

Highest-signal resume keywords

AI/ML Systems ExperienceLLM API IntegrationWorkflow Orchestration ToolsAWS/GCP/Azure DeploymentStrong Programming Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringMachine Learning ModelsDecision EnginesAPI IntegrationsEvent Driven ArchitectureObservability and MonitoringPrompt EngineeringDistributed SystemsVector DatabasesRAG Systems

Soft Skills

Problem SolvingSystem Thinking

Industry Keywords

Automation SolutionsAI SystemsData Privacy ComplianceSecurity PoliciesInternal Tool Integration

Tech Stack

Tools & technologies

AWSAzureDistributed SystemsGoogle Cloud Platform

About the role

Key responsibilities & impact

Design & deploy AI powered automation solutions using LLMs, machine learning models, and decision engines.
Build agent-based systems, prompt pipelines, and retrieval augmented generation workflows.
Develop autonomous or semi-autonomous systems that can take actions across internal tools and APIs.
Create scalable workflow automation using APIs, event driven architecture, and orchestration frameworks.
Integrate AI systems with internal platforms.
Develop reusable automation components and internal tooling.
Write clean, maintainable, production ready code.
Build observability, logging, guardrails, and monitoring into AI systems.
Ensure reliability, security, and responsible AI implementation.
Measure performance impact.
Continuously refine prompts, workflows, and models.
Identify new automation opportunities across the organization.
Implement guardrails, access controls, and safety mechanisms.
Ensure compliance with data privacy and security policies.
Partner with security teams on safe AI deployment.

Requirements

What you’ll need

4+ years of software engineering experience
2+ years working AI/ML systems, LLMs, or intelligent automation.
Experience with LLM APIs (OpenAI, Anthropic, etc.)
Experience in vector databases and RAG systems
Experience workflow orchestration tools
Strong programming skills
Experience building API integrations and distributed systems.
Experience deploying systems in AWS, GCP, or Azure environments.
Strong problem solving and system thinking skills

Benefits

Comp & perks

medical
dental
equity
discretionary bonuses