ApplySarthiApplied AI Demo Engineer
Anthropic
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1,110 open applied roles across 164 companies are on ApplySarthi right now, most of them in Bengaluru (102), Hyderabad (10), Delhi NCR (6).
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What applied roles keep asking for: Python (68%), Machine learning (52%), LLMs (39%), Java (37%), C++ (35%), Deep learning (27%), AWS (24%), Generative AI (20%) — counted across their open postings here.
LLMs jobs · Python jobs · Supply chain jobs · TypeScript jobs
Anthropic has 668 open roles listed here.
- Staff+ Software Engineer, VectorDB
- 3P Revenue Accounting & Reporting
- Audit, Security GRC
- Customer Success Manager
- Head of GTM Programs EMEA
Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for applied roles keep coming back to Python, Machine learning, LLMs, Java. Practise those questions before you sit with Anthropic.
Questions you are likely to be asked
- Why do you want to join Anthropic?
- What is your experience with LLMs? Tell me one thing you learned the hard way.
- Walk me through a model you built, from the data to how it was used.
- How did you know your model was actually good, and not just good on your test set?
- Tell me about a time the data was messy or wrong. What did you do?
Prep Sarthi gives you a free mock interview: an AI interviewer asks you questions like these out loud, from your own CV and this job, and shows your score and your weakest answer.
Practise the Applied AI Demo Engineer at Anthropic interview free →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 customer-facing teams are often the first place a customer sees what Claude can do. As a Demo Engineer, you'll build the demos, reference implementations, and reusable tooling that help those teams make new capabilities tangible, relevant, and trustworthy, ideally within days of a product launch rather than weeks after.
This role sits between product engineering, technical storytelling, and GTM execution. You'll own ambiguous, high-leverage problems end to end: prototyping an agentic experience for a new capability, then hardening it into something reliable that other teams can run on their own. You'll work closely with Product, Engineering, Marketing, Operations, and our sales and solutions teams, and you'll bring what you learn from customer-facing work back to the people building the products.
Because a demo is frequently someone's first impression of what our models can and can't do, accuracy and honesty matter as much as polish. Success in this role looks like customer-facing teams demonstrating new capabilities sooner and with more confidence, recurring requests becoming reusable assets rather than one-off projects, and field insights shaping product and launch-readiness decisions.
Responsibilities
- Own demo readiness for new and priority Claude capabilities, including environments, integrations, synthetic data, evaluations, reliability checks, and fallback paths
- Build prototypes, agents, and reference flows that make complex capabilities concrete and tie them to clear customer outcomes
- Turn recurring requests into reusable accelerators such as companion apps, templates, Skills, plugins, and self-service demo packages that scale across customer-facing teams
- Partner with GTM colleagues on high-impact customer moments, unblock critical technical gaps, and spot the patterns worth turning into shared assets
- Build internal agentic systems that automate demo preparation, validation, and asset maintenance, so demos stay current as products change
- Translate patterns from customer-facing work into product feedback, launch-readiness priorities, and systemic improvements with Product and Engineering
- Define and raise the bar for demo quality across accuracy, safety, reliability, usability, and adoption
- Decide when a customer need calls for a bespoke build and when it should become a shared capability
You may be a good fit if you have
- Proficiency in Python or TypeScript, with experience shipping working software end to end
- Hands-on experience building applications or agents on top of LLM APIs, including prompting, tool use, and retrieval
- Experience designing integrations with third-party APIs, data sources, and services
- The ability to take an ambiguous capability or customer need to a working prototype quickly, and then make it reliable
- Clear communication of technical concepts to both technical and non-technical audiences, including sales and solutions teams
- Comfort collaborating across Product, Engineering, Marketing, Operations, and GTM teams
- Experience in a demo engineering, solutions engineering, sales engineering, forward deployed engineering, developer relations, or product engineering role
- A track record of building reusable internal tools, templates, or self-service assets that other teams adopted
- Hands-on experience with Claude Code, the Claude Agent SDK, the Model Context Protocol (MCP), Skills, or plugins
- Experience building evaluation or validation harnesses for AI systems, including reliability checks and graceful fallbacks
- Experience building always-on or scheduled agentic systems that automate internal workflows
- Experience building synthetic or sanitized datasets that make demos realistic without exposing sensitive information
- Front-end or product design skills that help demos feel polished and intuitive
- Experience supporting product launches or running launch-readiness programs
- A history of turning field feedback into concrete product input that influenced a roadmap
- A passion for making powerful technology safe and beneficial, and a commitment to representing model capabilities accurately and honestly
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.
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Listed on greenhouse · posted 2026-10-19. ApplySarthi collects openings and links to application pages; the role is advertised by Anthropic, not by us.