AI Automation Engineer

StockX

8h•$140,000 - $160,000

About The Position

We are seeking an AI Automation Engineer to design, build, and scale intelligent automation systems that improve operational efficiency, reduce manual effort, and unlock new capabilities across the business. This role sits at the intersection of engineering, applied AI, workflow automation, and systems integration. You will be responsible for identifying high-impact automation opportunities and delivering production grade AI-driven solutions that integrate seamlessly into our technology ecosystem. You will partner cross-functionally with Engineering, Operations, Product, Data, and Security, as well as business stakeholders to transform manual and repetitive processes into intelligent, scalable systems.

Requirements

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

Responsibilities

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.