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 an 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
- 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
- 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
(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.
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.
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.
Skills Required
- Bachelor's degree or equivalent combination of education, training, and experience
- Strong programming skills in Python or TypeScript
- Experience building and operating production applications
- Production experience with LLMs, including context engineering, agent development, MCP development, tool use, and evaluation frameworks
- Experience using evaluations and transcript analysis to identify and fix problems in LLM systems
- Working fluency with data, including SQL
- Ability to navigate ambiguity and ship without a detailed specification
- Passion for advancing safe, beneficial AI
- 8+ years of experience as a software engineer, ML engineer, forward deployed engineer, or similar
- Experience with Claude Code and the Claude Agent SDK
- Experience with go-to-market systems or working closely with a revenue team
- Experience growing a codebase with many contributors, through inner-source or open-source practices
- Applied machine learning and experimentation experience, including A/B testing, propensity models, recommendations, or causal analysis
- Exceptional communication skills with non-technical partners
Anthropic Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Anthropic and has not been reviewed or approved by Anthropic.
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Strong & Reliable Incentives — Pay is positioned as top-of-market for many technical roles through a mix of high base pay, equity, and occasional bonuses/signing incentives. Benefits like substantial monthly stipends and employer-paid protections further strengthen perceived total rewards.
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Healthcare Strength — Healthcare is described as comprehensive across medical, dental, and vision, with additional mental-health support. Coverage is framed as robust for employees and dependents, which can materially increase the value of the overall package.
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Parental & Family Support — Paid parental leave is described as notably generous, alongside fertility coverage and other family-oriented supports. These elements broaden the rewards package beyond cash compensation and can improve retention for caregivers.
Anthropic Insights
What We Do
Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.
