Solutions Architect, Applied AI (Beneficial Deployments)
San Francisco, CA | New York City, NYFull-TimeLeadAI / Data Science
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 Beneficial Deployments
- Beneficial Deployments ensures AI reaches and benefits the communities that need it most. We partner with nonprofits, foundations, and mission-driven organizations to deploy Claude in education, global health, economic mobility, and life sciences, focusing on raising the floor.
About the Role
- We're looking for a Solutions Architect to join Beneficial Deployments. This role combines technical expertise with deep relationship-building to help partners accelerate their impact through AI adoption and deployment. You'll be the primary technical advisor for partners across segments, driving engagements from discovery through deployment, and coordinating with segment leads and product engineers to deliver impact.
Responsibilities
- Serve as the primary technical advisor to mission-driven organizations throughout their Claude adoption journey—partnering with segment leads to understand requirements and translating them into impactful solutions from discovery through deployment
- Transform partners into AI-native organizations through Claude Code enablement and internal business process evolution, to empower them to operate more effectively and build for where AI capabilities are headed
- Design and lead cohort-based accelerators to scale our expertise and impact to multiple organizations simultaneously
- Identify patterns across partners and segments to inform what we build at the ecosystem level—MCPs, evals, and other cross-partnership infrastructure
- Create technical presentations, demos, and scalable technical content (documentation, tutorials, sample code) to accelerate partner adoption and self-service
- Travel occasionally to customer sites for workshops, technical deep dives, and relationship building
- Help shape team processes and culture as we scale from 1 to N
You Might Be a Good Fit If You Have
- 3+ years in technical role, ideally with customer-facing exposure (Solutions Architect, Customer Engineer, Sales Engineer, Technical Account Manager, Product Engineer)
- Experience working in or building trust with education, healthcare, scientific research, nonprofit, or other mission-driven organizations, understanding their unique challenges and constraints
- Familiarity with common LLM implementation patterns, prompt engineering, evaluation frameworks, agent frameworks, and retrieval frameworks
- A love of teaching, mentoring, and helping others succeed
- A scrappy mentality–comfortable wearing multiple hats, building from scratch, driving clarity in ambiguous situations, and doing whatever it takes to further the mission
- The annual compensation range for this role is listed below.
- For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
How we're different
- We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
- The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
