Senior Sales Engineer - Token Factory

Overview

This role is offered through a partner company based in Ireland seeking a Senior Sales Engineer specialized in Token Factory. The position plays a critical technical function, assisting clients with building and scaling AI inference workloads that demand high performance.

Key Responsibilities

• Conduct comprehensive technical discovery sessions with engineering teams, technical founders, and customer stakeholders to understand model specifics, traffic projections, latency needs, GPU economics, and system dependencies.
• Convert client goals into production-ready system architectures while identifying technical risks, scalability challenges, and latent dependencies early in the process.
• Collaborate closely with sales teams on strategic opportunities to provide architectural clarity, influencing deal direction, and avoiding misaligned technical commitments.
• Establish clear proof-of-concept (PoC) success metrics, including latency, time to first token, throughput, cost efficiency, and other relevant performance measures.
• Evaluate workload complexity to determine the necessary optimization, technical support, engineering involvement, and GPU resources.
• Facilitate structured Go/No-Go decisions to ensure PoCs are appropriately scoped, economically viable, and free from excessive customization or unexpected R&D demands.
• Identify common customer configuration and workload trends, quantify demand for advanced inference optimizations, and provide actionable feedback to Product and Engineering teams.
• Support platform capability development by translating real-world workload data and customer insights into product improvement opportunities.
• Ensure that strategic deals are sound from a technical perspective before allocating engineering resources, supporting predictable resource management and scalable solutions for customers.

Required Qualifications and Skills

• In-depth knowledge of AI inference systems and GPU-supported infrastructure with expertise in performance-critical environments.
• Practical experience managing LLM workloads and understanding architectural trade-offs in large-scale inference deployment.
• Hands-on familiarity with inference frameworks and libraries such as vLLM, SGLang, or TensorRT-LLM.
• Strong analytical skills regarding latency, throughput, cost, scalability, resource utilization, and architectural trade-offs.
• Experience engaging with engineering-driven organizations, technical founders, developers, or technically advanced customers.
• Confident customer-facing communication skills, including the ability to constructively challenge assumptions and negotiate technical decisions.
• Commercial awareness, with insight that engineering capacity is a strategic and limited resource that requires careful allocation.
• Proficiency in Python and knowledge of contemporary AI, APIs, MLOps, DevOps, and cloud technologies.
• Experience with technologies like OpenAI or Anthropic SDKs, LangChain, LangSmith, smolagents, FastAPI, Flask, Kubernetes, Docker, and Git is valuable.
• Familiarity with leading cloud AI platforms, including AWS SageMaker, Bedrock, Google Cloud Vertex AI, or Azure Machine Learning, is preferred.
• Ability to work efficiently in a dynamic, international setting with a high level of ownership and autonomy.

Additional Information

The company offers competitive pay and flexible remote working arrangements within Europe. Employees benefit from substantial autonomy, ownership, and opportunities for continuous learning and career advancement. The working culture emphasizes collaboration, innovation, and engineering excellence with a global team of seasoned professionals specializing in AI, software, and infrastructure. Team members have the chance to impact platform evolution significantly and solve challenging problems at the forefront of AI infrastructure.