Solutions Architect, Applied AI (Federal Civilian)
San Francisco, CA | New York City, NY | Washington, DCFull-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 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 federal civilian agencies 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 mission 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.
Responsibilities
- Partner with account executives 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 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 Claude Code, the Claude API, and Claude for Enterprise
- Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread 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 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 frequently to customer sites for workshops, technical deep dives, and relationship building
- Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns
- Partner with account executives 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 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 Claude Code, the Claude API, and Claude for Enterprise
- Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread 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 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 frequently to customer sites for workshops, technical deep dives, and relationship building
- Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns
You may be a good fit if you have
- Security clearance not required, but a plus
- Must have prior experience working with US federal agencies
- 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager
- Experience 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
- Experience designing scalable cloud architectures and integrating with enterprise systems
- Familiar 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
- Security clearance not required, but a plus
- Must have prior experience working with US federal agencies
- 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager
- Experience 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
- Experience designing scalable cloud architectures and integrating with enterprise systems
- Familiar 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
- 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.
