Design, build, and maintain custom-coded automations and internal tools. Collaborate with engineers and stakeholders to deliver robust, scalable solutions. Develop reinforcement learning systems and integrate AI tools into existing infrastructure.
Key Highlights
Key Responsibilities
Technical Skills Required
Nice to Have
Job Description
About Us:
At Near, we help top talent in Latin America find remote roles with US companies.
About the Role:
We're looking for an AI Automation Engineer (Data & Creative Systems) who combines solid software engineering fundamentals with a strong focus on cloud data infrastructure, reinforcement learning, and creative content automation. You'll design, build, and maintain custom-coded automations and internal tools, and collaborate with other engineers and stakeholders to deliver robust, scalable solutions.
This role requires someone proactive and solution-oriented, who is comfortable dealing with ambiguity, takes ownership of problems end-to-end, and delivers high-quality results in a fast-moving environment.
You Will:
- Design, implement, and maintain custom-coded automations and backend services for both Near and our clients.
- Build and manage data infrastructure on GCP, including data warehouses, pipelines, and integrations between systems.
- A primary focus will be building a 'Brand Brain' - a context layer that ingests product reviews, brand guidelines, and competitor ad libraries to ensure AI-generated content is indistinguishable from human-made creative
- Develop reinforcement learning systems that improve based on feedback, applying them to automation and content workflows.
- Build automations for creative content generation targeting platforms like Meta and TikTok, integrating AI tools to produce relevant, scalable outputs.
- Integrate AI tools into existing infrastructure, providing business context to the AI for more targeted and relevant outputs.
- Design, structure, and maintain relational databases; implement data migrations and integrations between systems.
- Write reliable, well-tested code and set up safe testing practices for new and existing features.
- Contribute to system and architecture design for automation and data-related projects.
- Collaborate closely with other automation engineers, stakeholders, and clients to clarify requirements and deliver solutions aligned with business needs.
- Continuously improve existing automations, identifying bottlenecks and proposing technical enhancements.
- Document architecture, workflows, and implementation details to enable knowledge sharing within the team.
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About You:
Your Background:
- Strong experience as a data engineer, software engineer, backend engineer, or AI/ML engineer with strong coding responsibilities.
- Solid experience with GCP, particularly for building and managing data infrastructure (e.g., BigQuery, Dataflow, Cloud Storage).
- Hands-on experience with reinforcement learning (RL) - designing feedback loops and deploying RL-based systems.
- Experience building automations for creative workflows, especially for generating content for platforms like Meta or TikTok.
- Expertise in AI-native development environments (e.g., Claude Code) and workflow orchestration platforms (e.g., n8n) to accelerate the build-to-deploy cycle
- Experience integrating AI tools into existing infrastructure and providing business context to the AI for more relevant outputs.
- Strong Python skills in data or backend contexts (e.g., data processing, ML pipelines, analytics).
- Experience working with relational databases (SQL), including schema design, queries, and data migrations.
- Strong understanding of software engineering fundamentals: system design, architecture, testing, and code quality.
- Comfortable working in Agile environments (Scrum or similar), collaborating in a distributed team.
- Excellent communication skills - comfortable working in a remote, English-speaking environment.
- Self-motivated, proactive, and accountable - you take ownership of outcomes and follow through.
- Able to work independently, manage ambiguity, and adapt to changing priorities without losing execution quality.
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Nice to Have:
- Strong experience working with Python to build and manage data or AI systems.
- Experience with other cloud platforms (AWS, Azure) in addition to GCP.
- Background with data-focused frameworks, data analytics, or data-intensive applications (e.g., dbt, Airflow, Spark).
- Familiarity with infrastructure concepts and system design beyond pure coding.
- Experience in automation-heavy environments (internal tooling, process automation, workflow orchestration).
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