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Applied AI Engineer, Public Sector

Label Your Data·$280,000 – $320,000

Primary stack

PythonTypeScript

Nice to have's

LLMsAdvanced prompt engineeringAgent developmentScalable cloud architecturesEnterprise systems integrationArtificial intelligenceMachine learningData science

Job description

About the Position

Applied AI Engineer, Public Sector

Washington, DC

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

Requirements

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 frameworks, transcript analysis, MCP, and deployment at scale
  • Experience deploying and operating software in air-gapped or classified environments
  • Experience designing scalable cloud architectures and integrating with enterprise systems
  • Background in artificial intelligence, machine learning, or data science
  • Ability to navigate ambiguity and execute across domains with intellectual openness, finding simple solutions to complex problems
  • High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity
  • Passion for advancing safe, beneficial AI systems through creative technical applications

We Offer

  • Annual Salary: $280,000-$320,000 USD
  • Competitive compensation and benefits
  • Optional equity donation matching
  • Generous vacation and parental leave
  • Flexible working hours
  • Lovely office space in San Francisco

About the Company

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

Deadline to apply: None. Applications will be reviewed on a rolling basis.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links-visit anthropic.com/careers directly for confirmed position openings.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

© Label Your Data. This job description was sourced from the employer's public career page. TheJob is not the employer — we index the posting and route candidates to the source. All content rights and hiring decisions belong to the employer.

Label Your Data provides secure and high quality data annotation services for Computer Vision or NLP applications since 2020. We help Data Scientists and AI Engineers streamline the dataset labeling and focus on model development.About Label Your Data:— Founded in 2020;— 200+ annotation experts in Europe, LATAM and Africa;— 98%+ annotation accuracy benchmark;— 55 supported languages;— PCI/DSS certified;— ISO/IEC 27001:2013 certified;— GDPR, CCPA and HIPAA-compliant;— HQs in North America, EU and Asia.Our experience spans over 20 industries including Automotive, Robotics, Agriculture, E-commerce, Retail, Healthcare, Manufacturing, Fintech and Insurance.Our core services include but are not limited to:— Image & video annotation: 2D boxes, OCR, object/action detection, polygons, key points, semantic segmentation, 3D cuboids;— Text annotation: classification, NER, intent & sentiment analysis, prompts creation, Q&A pairs generation;— Audio annotation: transcription, sentiment recognition;— Sensor data annotation;— Data classification & categorization;— Data entry;— Data collection;— Model validation.

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