Applied AI Engineer, Public Sector
anthropic Washington, DCEst. Est. USD 160,000–220,000 / yearMid
Estimated range based on role, country and industry — not published by the company.
Key requirements
- Python
- Typescript
- Machine Learning
- Llm
- 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 a member of the Applied AI team at Anthropic, you will be an Applied AI Engineer supporting a dedicated national security mission program. You will be the customer's trusted technical advisor, working closely with their engineering and mission teams as they build and ship new capabilities powered by Claude: advising on architecture design decisions, developing evaluation frameworks, and guiding them through the most cutting-edge implementation patterns for LLMs.
Working closely with our Sales, Product, and Engineering teams, you'll guide the customer from technical discovery through successful deployment, much of it on-site in secure environments. You'll combine deep engineering expertise and cyber domain knowledge with customer-facing skills to help the customer unlock the full potential of Claude and move their mission capabilities closer to the frontier, while maintaining our high standards for safety and reliability.
Responsibilities
Serve as a specialist technical advisor for one or more national security mission programs, from discovery and evaluation through deployment and adoption, coordinating internally across multiple teams to drive customer success
Support the customer as they build with Claude Code, the Claude API, and Claude for Enterprise
Partner with account executives and Applied AI Architects to translate mission requirements into technical solutions
Influence technical architecture decisions and integration into the customer's existing stack by developing customized pilots, prototypes, and evaluation suites
Help develop evaluation frameworks to measure Claude's performance for mission-specific use cases
Lead hands-on technical workshops and code reviews with customer engineering teams
Identify common design patterns and contribute insights back to our Product and Engineering teams
Create and deliver technical content, from engineering deep dives to executive briefings
Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks
Work primarily on-site with the customer's engineering and mission teams in secure government facilities, while maintaining close internal coordination and feedback with Anthropic's Applied AI and Engineering teams
Minimum qualifications
Active TS/SCI clearance with Polygraph
Prior experience working within US intelligence community agencies as a government civilian or cleared contractor
4+ years of experience in technical roles such as Forward Deployed Engineer, Product Engineer, Software Engineer, or Technical Product Manager, with a desire to work closely with customers
Strong programming skills with proficiency in Python or TypeScript and experience building production applications
Hands-on expertise in one or more of the following domains:
Offensive or defensive cyber operations (including vulnerability research, reverse engineering, and ICS/OT security)
Cryptography and cryptanalysis
Intelligence analysis and ISR (all-source, SIGINT, GEOINT)
Mission and weapons systems (command and control, space, electronic warfare, autonomy)
CBRN and nonproliferation
Accreditation of classified systems (RMF, ATO, cross-domain solutions)
Exceptional communication skills to convey technical concepts to diverse stakeholders, from engineers to executives, while maintaining a low ego and collaborative approach
Preferred qualifications
Production experience with LLMs, including advanced prompt engineering, agent development and frameworks, evaluation frame
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