AI Automation Engineer

Job Purpose:
To design, build, scale, and maintain our core automation infrastructure. In this role, you will act as the bridge between unstructured AI capabilities (LLMs, RAG pipelines, intelligent agents) and structured enterprise systems (HRIS, Payroll, databases, and third-party APIs).

Your primary focus will be owning our n8n orchestration platform or relevancies, ensuring that our high-volume workflows, automated data processing pipelines, and AI-driven assistants run with enterprise-grade reliability, security, and precision.

Job Duties:

1. Develop Automation Frameworks

• Design, implement, and maintain scalable automation frameworks for test environments or production processes.

1. Workflow Architecture & n8n Management

• Own, scale, and maintain our self-hosted n8n production instances (Docker, PostgreSQL, environment configuration).
• Design modular, resilient, and high-performance multi-node n8n workflows utilizing advanced patterns (sub-workflows, error handling, batch processing, custom JavaScript/Python code nodes).
• Establish version control, CI/CD pipelines, and rigorous testing practices for all workflow updates.

1. AI Backbone & Agent Integration

• Integrate LLM APIs (OpenAI, Anthropic) into business workflows for automated parsing, sentiment analysis, document processing, and decision support.
• Build and maintain Retrieval-Augmented Generation (RAG) pipelines, managing vector databases (e.g., pgvector, Pinecone, Qdrant) for internal knowledge bases and HR/policy search.
• Enforce deterministic guardrails, structured JSON outputs, and validation steps around non-deterministic AI outputs before writing data to databases.

1. System Integrations & Data Pipelines

• Connect disparate platforms via REST APIs, GraphQL, webhooks, and secure authentication protocols (OAuth2, JWT, API Keys).
• Build robust data transformation pipelines to clean, map, and sync data seamlessly between operational tools and internal databases.
• Implement comprehensive logging, monitoring, and automated alerting for workflow failures or API rate-limit bottlenecks.

1. Documentation & Reporting

• Document automation procedures, test plans, and test scripts.
• Report on the outcomes of automated tests, including any issues or bugs.

1. Collaboration

• Work closely with developers, QA engineers, and DevOps to identify automation opportunities.
• Provide technical support and training to other team members regarding automation best practices.

Required Skill Set:

1. Programming & Data: Strong proficiency in JavaScript / Node.js and Python for custom data manipulation inside code nodes.
2. Solid understanding of SQL and working with relational databases (PostgreSQL).
3. AI & LLM Orchestration: Practical experience integrating LLM APIs, enforcing structured JSON schemas, RAG architectures.
4. Infrastructure & DevOps: Proficient with Docker, containerized deployments, environment management, self-hosted server maintenance.
5. API Integrations: Deep experience designing, debugging, and consuming REST APIs, handling webhooks.