Applied AI, Research Engineer

Anthropic•San Francisco, CA

1d•$300,000 - $400,000•Hybrid

About The Position

As an Applied AI Research Engineer, you will discover what Anthropic's models and products can do, prove it with real customers, and equip the rest of Applied AI to sell and deliver it. You'll embed with product teams to build deep expertise on new capabilities as they develop, and serve as a critical feedback loop carrying field reality back to Product and Research so that what we build next reflects what customers actually need. In collaboration with Sales, Product, and Research teams, you'll sit at the intersection of what we build and how customers adopt it. You'll own the technical<> GTM handshake for model and product launches: testing new models to understand their strengths and limitations, building demos and evals, and helping field teams get ready. When strategic customers hit novel challenges, you'll go hands-on to solve them. And throughout, you'll synthesize what you're learning across customers and products into insights that shape our roadmap, working closely with Product, Engineering, and Research teams to stay calibrated on what's working, what's not, and what matters most. This role is equal parts researcher, field expert, and connective tissue between our customers and the teams that build our products. You'll need the technical depth to push the boundaries of what our models can do, strong communication skills to make complex capabilities clear to diverse audiences, and the instinct to turn what you learn in the field into signal that makes our products better.

Requirements

6+ years of experience as a Software Engineer, Technical Product Manager, Forward Deployed Engineer, AI startup founder, or similar technical role -- ideally with some exposure to customers or end users
A track record of going deep on technical problems and then translating what you learned into materials, training, or tools that helped others succeed
Strong technical aptitude with strong proficiency in at least one programming language
Meaningful experience building with large language models -- whether shipping LLM-powered products, developing agents or workflows, or integrating models into production systems
Experience designing evals, building prototypes, or developing technical enablement for complex products
The ability to quickly build domain expertise in new product areas and become a credible technical voice on new topics
Curiosity about what AI models can actually do -- you enjoy probing the edges of new capabilities and figuring out what use cases just unlocked
Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders, including exec-level
The ability to navigate and execute amidst ambiguity, and to flex into different domains based on the business problem at hand, finding simple, easy-to-understand solutions
A collaborative, service-oriented mindset – go-to-market at Anthropic is a team sport
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

Responsibilities

Embed with product teams to build deep technical expertise on new products and capabilities as they develop, becoming the field's go-to expert in your domain
Own the technical<> GTM handshake for model and product launches-- early testing, field readiness assessments, and ongoing capability education throughout the model lifecycle
Build demos, evals, and prototypes that showcase customer-relevant model and product capabilities, and define what good performance looks like in important domains
Develop enablement materials like playbooks, training sessions, and reference architectures in partnership with Technical Enablement, so Applied AI teams can effectively position and deliver new capabilities from day one
Engage hands-on with strategic customers facing novel technical challenges in your domain, discover solutions, then package learnings into scalable approaches for the broader field
Synthesize insights from across customer engagements and work with Product and Research to land them. Identify adoption patterns, common blockers, and capability gaps that should inform our research and product roadmaps
Partner with Sales and Applied AI teams to support high-value accounts that need specialized domain knowledge
Travel occasionally to customer sites for workshops, implementation support, and research collaboration