资深人工智能工程师,GTM分类
Staff AI Engineer, GTM Claudification
关于Anthropic
Anthropic的使命是创造可靠、可解释且可引导的AI系统。我们希望AI对我们的用户以及整个社会都是安全且有益的。我们的团队是一个快速发展的由致力于研究、工程、政策专家和商业领袖组成的小组,共同构建有益的AI系统。
关于该职位
作为GTM Claudification团队的资深AI工程师,你将构建运行Anthropic自身市场推广工作的代理和AI系统。我们的销售团队每天都在与代理协作。你将把工作推进到下一步,构建能够在诸如内部销售、外部销售和管道管理等区域实现完全自主操作的代理。此外,你还将构建评估框架,证明这些代理已准备好面向客户的工作,并且在创造价值。这是一个高级职位,你将推动整个团队在代理和评估方面的技术方向。
与销售团队、RevOps以及我们的平台工程合作伙伴紧密合作,你将从最初的原型到生产运营全程负责项目。你将结合全栈工程(MCP服务器、代理系统、网页应用等)与实际的评估工作(行为基准测试、生产监控、投资回报率测量),并帮助构建由我们市场推广部门各处的开发者所贡献的共享平台。你曾在注重分析严谨性的文化中工作过,并渴望在公司成长的关键时刻,帮助塑造AI工程职能的规范和最佳实践。
主要职责
- 构建并运营能够端到端运行市场推广动作的自主代理,涵盖内部销售、外部销售、管道管理和客户互动等领域
- 为每个动作设计人工监督机制:审批节点、交接流程和升级路径,确保销售团队保持控制权
- 开发代理行为的评估框架,并在开发和生产环境中运行
- 在生产环境中对模型和工具调用进行监控,并构建可观测性和度量体系,将代理行为与销售管道和收入联系起来
- 发布MCP服务器、代理技能和连接至CRM、通讯工具和数据仓库等系统的网页应用
- 设定团队内如何构建、评估和运营代理的技术方向
- 构建由市场推广部门各处开发者所贡献的共享代码库,制定保持高质量的规范和审查实践
- 直接与销售团队、RevOps和我们的平台工程合作伙伴紧密合作
查看英文原文
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 Staff AI Engineer on the GTM Claudification team, you will build the agents and AI systems that run Anthropic's own go-to-market work. Our sellers already work alongside agents every day. You will take things to the next step and build agents that run complete autonomous motions across areas like inbound, outbound, and pipeline management. In addition, you’ll build eval frameworks that prove those agents are ready for customer-facing work and are driving value. This is a senior role where you’ll drive technical direction for agents and evals across our team.
Working closely with sellers, RevOps, and our platform engineering partners, you'll own projects from first prototype through production operation. You'll combine full-stack engineering (MCP servers, agentic systems, web applications, etc.) with hands-on evaluation work (behavior benchmarks, production monitoring, ROI measurement), and help architect the shared platforms that builders from across our go-to-market org contribute to. You've worked in cultures of analytical rigor before, and you're eager to help shape the norms and best practices of a growing AI engineering function at a pivotal moment in the company's growth.
Key responsibilities
- Build and operate autonomous agents that run go-to-market motions end to end, across areas like inbound, outbound, pipeline management, and customer engagement
- Design the human oversight for each motion: approval gates, handoffs, and escalation paths that keep sellers in control
- Develop evaluation frameworks for agent behavior, and run them in development and in production
- Instrument model and tool calls in production, and build the observability and measurement that ties agent actions to pipeline and revenue
- Ship MCP servers, agent skills, and web applications that connect to systems like our CRM, communication tools, and data warehouse
- Set the technical direction for how we build, evaluate, and operate agents across the team
- Architect shared codebases that builders from across go-to-market contribute to, setting the conventions and review practices that keep quality high
- Work directly with sellers to ground agent designs in real workflows, and iterate based on what you observe
- Identify repeatable patterns and contribute insights back to Anthropic's Product and Engineering teams
- Maintain strong knowledge of the latest developments in LLM capabilities, agent frameworks, and evaluation techniques
Minimum qualifications
- Strong programming skills in Python or TypeScript, with experience building and operating production applications
- Production experience with LLMs, including context engineering, agent development, MCP development, tool use, and evaluation frameworks
- Experience using evals and transcript analysis to find and fix real problems in an LLM system
- Working fluency with data, including SQL
- Ability to navigate ambiguity and ship without a spec, finding simple solutions to complex problems
- Passion for advancing safe, beneficial AI, and care for the people who use what you build
Preferred qualifications
- 8+ years in roles such as software engineer, ML engineer, or forward deployed engineer. Former technical founders are encouraged to apply
- Experience with the Claude Code and the Claude Agent SDK
- Experience with go-to-market systems (CRM, sales engagement, enrichment, conversation intelligence) or time working closely with a revenue team
- Experience growing a codebase that many people contribute to, inner-source or open-source
- Applied ML and experimentation background: A/B testing, propensity models, recommendations, or causal analysis
- Exceptional communication skills to convey technical concepts to non-technical partners with low ego
Representative projects
(Illustrative of the kind of work, not a project list.)
- Build an agent that takes a routine sales workflow from first signal to a drafted, human-reviewed action
- Stand up the eval suite for an agent: seed scenarios, scoring rubrics, and regression runs on every change
- Ship an MCP server that gives sellers and their agents governed access to a core revenue system
- Design a shared repository where go-to-market builders publish agents and skills, with the tests and review rules that keep it healthy
- Build a predictive model that explains itself, so an agent can tell a seller why it suggests an action
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.
Annual Salary:
$320,000—$405,000 USD
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.