About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the role

As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping large enterprises understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex business challenges while maintaining our high standards for safety and reliability.

Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems.

Key responsibilities

Partner with account executives across South Korea to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation

Serve as the primary technical advisor to enterprise customers across South Korea throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success

Support customers building with both the Claude API and Claude for Work

Create and deliver compelling technical content tailored to different audiences across South Korea. You will need to be able to run the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives

Guide technical architecture decisions and help customers across South Korea integrate Claude effectively into their existing technology stack

Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases

Identify common integration patterns and contribute insights back to our Product and Engineering teams

Travel occasionally to customer sites for workshops, technical deep dives, and relationship building

Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns

Minimum qualifications

Experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager

Native-level Korean fluency and business-level English required

Experience working with enterprise customers, navigating complex buying cycles involving multiple stakeholders

Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more

Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders

Preferred qualifications

5+ years of relevant experience

Experience designing scalable cloud architectures and integrating with enterprise systems

Comfortable with python

Familiarity with common LLM frameworks and tools or a background in machine learning or data science

Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities

A love of teaching, mentoring, and helping others succeed

Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities

Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems