AI Engineer

• Design, develop, and deploy AI/ML models for production environments.
• Build and optimize AI-powered applications using large language models (LLMs) and generative AI tools.
• Develop intelligent automation workflows, chatbots, recommendation systems, and predictive analytics solutions.
• Fine-tune, evaluate, and improve machine learning models for performance and scalability.
• Collaborate with software engineers and product teams to integrate AI features into existing platforms.
• Work with structured and unstructured datasets for training and inference pipelines.
• Implement prompt engineering strategies and retrieval-augmented generation (RAG) systems.
• Monitor AI systems, troubleshoot issues, and continuously improve model accuracy and efficiency.
• Stay updated with the latest advancements in AI, machine learning, and automation technologies.
• Maintain documentation for AI models, systems, and workflows.

• Build and extend the eval pipeline: how we measure task completion, catch regressions, and turn production failures into fixed behaviors.
• Work on context management: what the agent sees, when, and how we keep long-horizon tasks coherent without burning tokens.
• Design sub-agent patterns: when to fan out, how to compose specialized agents cleanly, and how to keep the parent agent in control of the outcome.
• Own document parsing: turning supplier-uploaded invoices, catalogs, and contracts into structured context the agent can reason over.
• Wrap Coupa supplier APIs as agent-callable CLI tools, with clean error surfaces and sensible defaults for an agent caller.
• Ship supplier-facing skills on top of the harness: the procedural instructions and tool compositions that let the agent handle specific tasks end-to-end.
• Debug messy production behavior: why did the agent take that path, where did it get confused, and what tool, context, or harness change fixes it?
• Partner with the senior engineer on harness architecture calls as you find gaps while working across the stack.

Lead AI Engineer

• Design and build the agent harness — skill loading, tool invocation, context management, the execution sandbox, compaction patterns and sub-agents.
• Stand up the evaluation pipeline: how we measure skill effectiveness, catch regressions, and turn production failures into fixed behaviors.
• Partner with product and engineering to ship the first 3–5 supplier-facing use cases (invoicing, catalog, strategic views) on top of the platform you build.
• Define and maintain the cloud deployment and configuration for the platform. How it gets to production, how it scales, and how it stays secure.
• Make architectural calls on runtime isolation, credential handling, audit logging, and tenant separation, in collaboration with DevOps specialists.
• Raise the bar for the rest of the team on how to build with agentic tooling, what to automate, what to verify, and what to leave to humans.

Senior Lead AI Engineer

• System Administration & Optimization: Administer and optimize key GTM platforms (e.g., Salesforce, Marketo, Outreach, Gainsight), ensuring data integrity, system scalability, and user adoption.
• Strategic Planning & Roadmapping: Collaborate with GTM leadership to define system requirements, evaluate new technologies, and develop a strategic roadmap for GTM systems to align with business objectives.
• Integration & Data Flow Management: Design, implement, and maintain integrations between various GTM systems and other business-critical platforms, ensuring accurate and timely data flow across the organization.
• Process Improvement & Automation: Identify opportunities for process automation and efficiency gains within GTM workflows, leveraging system capabilities to streamline operations and improve team productivity.
• User Support & Training: Provide expert-level support to GTM teams, troubleshoot system issues, and develop training materials to ensure users are effectively utilizing GTM tools.
• Reporting & Analytics: Develop and maintain dashboards, reports, and analytics to provide insights into GTM performance, system utilization, and data quality.
• Vendor Management: Manage relationships with GTM system vendors, including contract negotiation, service level agreements, and product roadmap discussions.
• Compliance & Governance: Ensure GTM systems adhere to data privacy regulations (e.g., GDPR, CCPA) and internal governance policies.
• Project Management: Lead and manage GTM systems projects from conception to completion, including requirements gathering, solution design, testing, and deployment.

CX Technology Lead – AI

• Diseñar y desarrollar modelos de Machine Learning para soluciones de ingeniería de alto impacto.
• Construir, entrenar y optimizar modelos de aprendizaje automático y profundo.
• Mantenerse al tanto de los últimos desarrollos en investigación y tecnología de AI/ML.
• Crear documentación completa de la arquitectura del modelo y procesos de entrenamiento.
• Presentar hallazgos y recomendaciones a audiencias técnicas y no técnicas.

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AI Engineer

Lead AI Engineer

Senior Lead AI Engineer

CX Technology Lead – AI

AI Engineer