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You will embed with strategic customers to build and deploy production-grade AI applications using Claude models. Additionally, you will identify repeatable deployment patterns and provide technical support to ensure successful enterprise AI adoption.
Requirements
Candidates must have 4+ years of experience in a technical, customer-facing role or software engineering with consulting experience. Proficiency in Python and experience with LLM production development are required, along with fluent English and French language skills.
Full job description
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.
As a member of the Applied AI team at Anthropic, you will be a Forward Deployed Engineer (FDE) who embeds directly with our most strategic customers to drive transformational AI adoption. You will collaborate closely with customer teams to ship advanced AI applications that solve real world business problems. Our FDEs engage with customers to accelerate the adoption of existing products and create new applications built on our models.
Working closely with our Post-Sales, Product, and Engineering teams, you'll combine engineering expertise, an understanding of frontier AI applications, and customer-facing skills to understand customer workflows and develop innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability.
You will sit at the frontier of enterprise AI deployments and serve as one of our founding FDEs who helps to shape our forward-deployed motion. We expect our FDEs to operate autonomously, thrive under ambiguity, and represent Anthropic at the highest level in customer environments. This is a significant responsibility: you’ll play a key role in championing our mission in the enterprise.
Responsibilities
Work within customer systems to build production applications with Claude models, ensuring that these products meet customer requirements.
Deliver technical artifacts for customers like MCP servers, sub-agents, and agent skills that will be used in production workflows.
Provide white glove deployment support for Anthropic products in enterprise environments.
Identify and codify repeatable deployment patterns and contribute insights back to our Product and Engineering teams.
Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks.
Build long term relationships with customers and proactively identify new opportunities for AI deployment throughout the lifecycle of an engagement.
Travel frequently (25-50%) to customer sites to build in person with customers.
Be a champion for Anthropic’s mission in the field.
You May Be a Good Fit If You Have
4+ years of experience in a technical, customer facing role such as Forward Deployed Engineer, or as a Software Engineer with consulting experience. Former technical founders are also encouraged to apply.
Native German speaker with fluent English proficiency
Production experience with LLMs including advanced prompt engineering, agent development, evaluation frameworks, and deployment at scale.
Strong programming skills with proficiency in Python (and ideally in one or more additional languages like TypeScript, Java, etc) and experience shipping production applications
High agency with an ability to navigate ambiguity present in complex organizations.
High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity.
Passion for advancing safe, beneficial AI systems through creative technical applications.
Strong communication skills to conduct discovery with customers and to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach.
A background in financial services, healthcare/life sciences, or another enterprise vertical is a plus.
Experience with enterprise IT systems and/or AI deployment patterns is a plus.
Logistics
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
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.
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.
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.
Come work with us!
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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Anthropic is an AI safety and research company working to build reliable, interpretable, and steerable AI systems.
Industry
Research Services
Company size
501-1,000 employees
LinkedIn followers
4,093,883
Total funding
$129B
We're an AI research company that builds reliable, interpretable, and steerable AI systems. Our first product is Claude, an AI assistant for tasks at any scale.
Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.
GamingEducationSoftwarePredictive AnalyticsInternet of ThingsOnline GamesManufacturingIncubatorsInformation TechnologyMedical Device
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