Strategic Overview
Staff+ Software Engineer, Enterprise Knowledge Work at Anthropic is a dev opportunity centered on the specialist responsibilities and outcomes described in the employer's listing.
The published role emphasizes work such as Own technical design and delivery for enterprise-facing core products, end-to-end across the stack Partner with product, design, and go-to-market to turn enterprise customer workflows into shipped product, not just execute against a spec.
The role is listed for San Francisco, CA / New York City, NY with the working arrangement published with the role, giving candidates the practical context needed to assess fit before applying.
Key information at a glance
About This Role
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.
Key Responsibilities & Objectives
- Own technical design and delivery for enterprise-facing core products, end-to-end across the stack
- Partner with product, design, and go-to-market to turn enterprise customer workflows into shipped product, not just execute against a spec
- Set technical direction and standards for your team: architecture, code quality, and how the team builds
- Work directly with enterprise customers and sales during key conversations, translating what you learn into engineering priorities
Required Qualifications & Candidate Blueprint
- 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
Salary & Benefits
Published compensation: $405,000 – $485,000 USD
Salary Benchmark
This role’s published compensation is compared with current employer-disclosed salary ranges for the same role at the Staff level in the same currency.
Benchmark uses active employer job postings in our database and excludes this listing. It is not a third-party salary estimate, and currencies are not converted.
Full Job Description
The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.
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
Anthropic's Enterprise Knowledge Work team builds the products that help enterprise knowledge workers collaborate deeply with Claude for major parts of their work.
Over the past year, AI has transformed how software engineering happens; for the rest of knowledge work, though, using AI still mostly means answering questions and producing first drafts — a small slice of the actual job.
We're building toward something bigger: people and agents working together on every core work objective, from first idea to finished product, and the recurring work of a team running with Claude in the loop instead of a person pushing every step. It's an enormous space, it's early, and no one has built it well yet.
You'll help decide what these products are, not just how they're built — the product questions are as open as the architecture ones — and you'll see your work land with real teams at the world's largest enterprises.
What you'll do
- Own technical design and delivery for enterprise-facing core products, end-to-end across the stack
- Partner with product, design, and go-to-market to turn enterprise customer workflows into shipped product, not just execute against a spec
- Set technical direction and standards for your team: architecture, code quality, and how the team builds
- Work directly with enterprise customers and sales during key conversations, translating what you learn into engineering priorities
- Work closely with research to make the models better in your domain: shaping evals, surfacing failure modes, and feeding customer learnings back into model development
- Mentor other engineers and raise the technical bar across the team, working with influence rather than authority
- Build the core primitives that enable knowledge workers across industries and roles to meaningfully leverage Claude
You may be a good fit if you
- Have 8+ years of software engineering experience, ideally with 2+ years at a Staff or equivalent technical leadership level
- Have led the design and delivery of complex customer-facing products across the full stack
- Have built AI products and know what it takes to turn model capabilities into applications people actually use
- Are comfortable working directly with enterprise customers and translating what you learn into technical decisions
- Have built products from 0 to 1 in fast-moving environments, and can set technical direction with limited precedent to lean on
- Drive cross-team alignment to ship impactful work, with influence over authority
Strong candidates may also have
- Experience working with research to improve domain-specific model capabilities, including evaluation frameworks
- Experience as startup founders or early-stage employees
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.
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.
Editor’s Market Perspective (Our Custom Analysis)
Why This Position Matters
This dev opening is a useful opportunity for candidates whose experience matches the role-specific capabilities named in the listing. Its strongest career signal is the scope of the work itself — particularly Own technical design and delivery for enterprise-facing core products, end-to-end across the stack — rather than a generic title alone.
Resume & Application Strategy
For the application, mirror the employer's language where it truthfully matches your background: foreground the role-specific capabilities named in the listing, quantify outcomes from comparable work, and place the most relevant experience near the top of the resume. If the listing specifies tools, platforms, leadership scope, or domain experience, use those exact terms in context instead of presenting an unrelated keyword list.
We organize source-provided information into this independent job-seeker overview. Compensation is shown only when the source provides it; the official listing remains the authority for current requirements and application instructions.