Senior AI Automation Engineer

Requirements3+ years of professional experience building integrations, automations, or workflow systemsStrong proficiency with low-code/no-code automation platforms (n8n,AI for business automation- Tray.ai, Zapier,Make | AI Workflow Automation Software & Tools ,or similar)Solid JavaScript skills -most automation logic happens in JavaScript nodes and custom functionsHands-on experience with LLM APIs (OpenAI, Anthropic Claude, or similar) and prompt engineeringExperience working with REST APIs, webhooks, and authentication patterns (OAuth, API keys, JWT)Understanding of data transformation and formats (JSON, XML, CSV)Ability to read API documentation, debug integration issues, and troubleshoot automation failuresExperience building event-driven workflows and handling asynchronous processesStrong problem-solving skills and ability to translate business requirements into technical solutionsSelf-motivated, disciplined, and comfortable working independently across time zonesGreat communication skills - ability to explain technical concepts to non-technical stakeholdersYour English is at least at the Upper-Intermediate level to communicate with our teamsPreferred Skills/AbilitiesExperience building AI agents or multi-step LLM workflows (LangChain, CrewAI, AutoGen, or custom implementations)Python scripting for data processing, API integration, or ETL workflowsFamiliarity with workflow orchestration tools or iPaaS platforms (Temporal, Workato, MuleSoft)Understanding of vector databases and semantic search for RAG implementationsExperience with freight, logistics, or supply chain systems and terminologyKnowledge of SQL and database queries for data analysisBackground in operations, RevOps, data engineering, or technical product rolesExperience measuring and optimizing automation ROI (cost per call, error rates, processing time)Experience with cloud platforms (AWS, Azure or GCP) and serverless architecturesUnderstanding of microservices architecture and event-driven systemsResponsibilitiesDesign and deploy AI-powered automation workflows using low-code platforms and custom JavaScriptBuild intelligent systems that leverage large language models (LLMs) for decision-making, data extraction, and process automationCreate and maintain integrations between internal systems and third-party platforms using APIs, webhooks, and event-driven architecturesDevelop data pipelines that transform, enrich, and route information across multiple systems and data sourcesImplement prompt engineering strategies and design multi-step LLM orchestration workflowsBuild and optimize automated workflows that eliminate repetitive manual tasks across operations teamsMonitor automation health, debug failures, and continuously optimize workflows for reliability, performance, and cost-efficiencyIdentify new automation opportunities by collaborating directly with operations, product, and engineering teamsDocument workflows, create runbooks, and establish best practices for scalable AI automationParticipate in code reviews and contribute to shared automation libraries, frameworks, and templatesMeasure and report on automation performance metrics, including accuracy, latency, cost savings, and operational impactPrototype new AI capabilities and experiment with emerging technologies as part of our Technical Innovation ProgramExample Projects & Initiatives To give you a sense of the types of challenges you'll tackle, here are examples of projects our AI Automation Engineers work on:Intelligent Document Processing:Build systems that automatically extract structured data from unstructured documents (PDFs, emails, images)Create validation workflows that use AI to verify data accuracy and flag anomalies for human reviewDesign document classification systems that route different document types to appropriate processing pipelinesImplement OCR + LLM workflows that handle handwritten or poorly scanned documentsAI-Powered Business Process Automation:Develop AI agents that conduct multi-step research and qualification processes autonomouslyBuild conversational systems that handle routine inquiries and escalate complex cases appropriatelyCreate intelligent routing and matching systems that optimize business outcomes using historical data and ML modelsDesign automated scheduling and coordination systems that handle complex business logic and constraintsSystem Integration & Data Orchestration:Connect internal platforms with external third-party services, handling authentication, rate limiting, and error recoveryBuild real-time data synchronization pipelines that keep multiple systems consistentCreate webhook listeners and event processors that trigger automated workflows based on external eventsDesign data enrichment pipelines that pull information from multiple sources and merge it intelligentlyOperational Intelligence & Monitoring:Build automated alerting and notification systems that detect anomalies and trigger appropriate responsesCreate dashboards and reporting workflows that aggregate data from multiple sourcesDevelop predictive systems that use historical patterns to forecast operational needsDesign automated quality control systems that continuously validate data accuracy across systemsAI Innovation & Experimentation:Prototype new AI capabilities using the latest LLM models and techniquesExperiment with vector databases, semantic search, and retrieval-augmented generation(RAG)Build proof-of-concepts that demonstrate the business value of emerging AI technologiesContribute to our Technical Innovation Program (TIP) with novel automation approachesPlatform & Infrastructure:Develop reusable automation components, templates, and design patternsCreate internal tooling that makes it easier for other teams to build and deploy automationsEstablish monitoring, logging, and observability standards for automation workflowsBuild testing frameworks that ensure automation reliability and catch regressionsThese projects span multiple teams and business functions - you'll have the opportunity to work on whatever creates the most business value, from carrier operations to customer experience to internal productivity tools.