Prompt Engineer Jobs
Prompt Engineer jobs are open across AI research, enterprise software, healthtech, fintech, and media, from junior to staff and principal levels, with specializations in LLM fine-tuning, retrieval-augmented generation, and conversational AI. Find a role that fits from the openings below and apply directly.
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Showing 5 of 13+ Prompt Engineer jobs
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:
The Encodings Infra team maintains the libraries that engineers and researchers across Anthropic use to encode text and multimodal data into a form that Claude can consume. It also determines Claude’s prompt shape: how a user’s turn is represented to the model, how Claude calls tools and receives tool results, and so on.
As a Software Engineer on this team, you'll own the design and maintenance of these libraries—keeping their APIs intuitive, their performance sharp, and their abstractions solid enough that most of the org never has to think about encodings or prompt structures at all. You’ll have the satisfaction of knowing that your work enabled Claude to learn new ways of understanding the world.
This role is unusually broad: your work will touch systems across the codebase, from pretraining to finetuning to the API, and you'll collaborate closely with both researchers and engineers to make sure new encoding ideas can move quickly from experiment to production.
Responsibilities:
Maintain and improve the encoding libraries used by engineers and researchers across Anthropic
Run experiments to determine the optimal way to feed structured data into Claude without confusing it
Design data structures and abstractions that shield most of the organization from the details of how encoded data works while enabling “power users”
Adapt the encoding libraries to support new research directions as they emerge, and make sure that we can ship these research ideas to production
Optimize encoding performance across the systems that depend on these libraries
You may be a good fit if you:
Have 5+ years of software engineering experience, with meaningful time spent maintaining libraries, SDKs, or developer-facing APIs
Have familiarity with ML terminology and LLM architecture — you don't need to be an ML expert, but enough understanding to work effectively alongside researchers and understand the results of experiments
Have experience carrying out complex refactors in large codebases
Have strong communication skills and enjoy working closely with researchers and engineers to understand what they need
Are results-oriented, with a bias towards flexibility and impact
Pick up slack, even if it goes outside your job description
Care about the societal impacts of your work
Strong candidates may also have experience with:
Tokenizers or other text/data encoding systems
Maintaining a widely-used library over a long period of time
Performance optimization
Python and/or Rust
Reinforcement learning or model training infrastructure
Representative projects:
Working with a research team to ship a new multimodal data type (audio, video, etc) to production
Redesigning a core abstraction so that we can change how data is encoded into Claude without breaking downstream teams
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.
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:
The Encodings Infra team maintains the libraries that engineers and researchers across Anthropic use to encode text and multimodal data into a form that Claude can consume. It also determines Claude’s prompt shape: how a user’s turn is represented to the model, how Claude calls tools and receives tool results, and so on.
As a Software Engineer on this team, you'll own the design and maintenance of these libraries—keeping their APIs intuitive, their performance sharp, and their abstractions solid enough that most of the org never has to think about encodings or prompt structures at all. You’ll have the satisfaction of knowing that your work enabled Claude to learn new ways of understanding the world.
This role is unusually broad: your work will touch systems across the codebase, from pretraining to finetuning to the API, and you'll collaborate closely with both researchers and engineers to make sure new encoding ideas can move quickly from experiment to production.
Responsibilities:
Maintain and improve the encoding libraries used by engineers and researchers across Anthropic
Run experiments to determine the optimal way to feed structured data into Claude without confusing it
Design data structures and abstractions that shield most of the organization from the details of how encoded data works while enabling “power users”
Adapt the encoding libraries to support new research directions as they emerge, and make sure that we can ship these research ideas to production
Optimize encoding performance across the systems that depend on these libraries
You may be a good fit if you:
Have 5+ years of software engineering experience, with meaningful time spent maintaining libraries, SDKs, or developer-facing APIs
Have familiarity with ML terminology and LLM architecture — you don't need to be an ML expert, but enough understanding to work effectively alongside researchers and understand the results of experiments
Have experience carrying out complex refactors in large codebases
Have strong communication skills and enjoy working closely with researchers and engineers to understand what they need
Are results-oriented, with a bias towards flexibility and impact
Pick up slack, even if it goes outside your job description
Care about the societal impacts of your work
Strong candidates may also have experience with:
Tokenizers or other text/data encoding systems
Maintaining a widely-used library over a long period of time
Performance optimization
Python and/or Rust
Reinforcement learning or model training infrastructure
Representative projects:
Working with a research team to ship a new multimodal data type (audio, video, etc) to production
Redesigning a core abstraction so that we can change how data is encoded into Claude without breaking downstream teams
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.
See All 13 Prompt Engineer Jobs
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Find Prompt Engineer JobsPrompt Engineer Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software
- Artificial Intelligence
What Employers Look For
The qualifications that appear most often in prompt engineer jobs.
- Hands-on experience designing and iterating prompts for large language models in production environments
- Proficiency with at least one LLM API such as OpenAI, Anthropic, or Google Vertex AI
- Familiarity with prompt chaining frameworks like LangChain, LlamaIndex, or equivalent tools
- Ability to build and interpret evaluation datasets to measure model output quality and reliability
- Experience with retrieval-augmented generation architectures and vector database integration
- Bachelor's degree in computer science, linguistics, or a related field or equivalent demonstrated experience
Tips for Your Prompt Engineer Job Search
Tailor your resume to model families
List the specific model families you've worked with, such as GPT-4, Claude, Gemini, or open-source alternatives like Llama. Recruiters and hiring managers scan for these names first, so generic 'AI experience' language won't surface your resume in filtered searches.
Show prompt artifacts, not just outcomes
Employers want to see your actual prompts, evaluation rubrics, and iteration logs, not just the features they powered. Link a public GitHub repo or portfolio page that includes redacted but real prompt chains and your reasoning behind design choices.
Filter openings by stack before applying
Prompt engineering roles vary sharply by toolchain. A role built around LangChain and vector databases requires a different story than one centered on system-prompt governance for a proprietary model. Read the tech stack in each listing and match your application language to it.
Apply early to roles that fit
Migrate Mate lists prompt engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare a live prompt engineering exercise
Many interviews now include a timed prompt construction task using a real model. Practice writing, testing, and refining prompts under constraints, including token limits and output format requirements, so you can narrate your reasoning clearly while working in real time.
Negotiate scope alongside compensation
Prompt engineer roles vary widely in autonomy, from executing specs handed down by ML engineers to owning the entire evaluation pipeline. Before accepting, clarify whether you'll define the evaluation criteria or only execute them, since that distinction shapes your career trajectory significantly.
Prompt Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most prompt engineers?
The companies hiring the most prompt engineers right now include BEAM, Adobe, and Photon, with the largest share of openings in Texas, Florida, and Virginia, based on current listings on Migrate Mate as of September 2026. Hiring is concentrated at AI-native companies, large enterprise software firms, and media organizations building generative content tools.
How many prompt engineer jobs are remote?
About 56% of prompt engineer openings are fully remote or hybrid as of September 2026, reflecting the role's strong alignment with distributed engineering teams. Roles focused on conversational AI design, evaluation pipeline ownership, and LLM integration tend to offer the highest share of fully remote arrangements, while positions embedded in product or research labs more often require on-site presence.
How do you become a prompt engineer?
Start by building hands-on fluency with at least one major LLM API, then practice designing prompts for defined tasks and evaluating outputs systematically against clear criteria. Develop a public portfolio of prompt chains and evaluation rubrics that demonstrates your reasoning process. From there, target roles at companies actively shipping LLM-powered products, where applied prompt work is central rather than incidental to the job.
Can you get hired as a prompt engineer without direct experience?
Yes, candidates without formal job titles in prompt engineering get hired by demonstrating a strong portfolio of real prompt work, even from personal projects or open-source contributions. Focus on building evaluation datasets, documenting your iteration logic, and showing familiarity with a production-relevant toolchain. Roles labeled 'AI specialist,' 'LLM developer,' or 'conversational AI designer' often have overlapping skill requirements and lower competition than those using the prompt engineer title explicitly.
What does the prompt engineer interview process look like?
Most processes include an initial screen focused on your familiarity with LLM APIs and past projects, followed by a technical exercise where you design or debug prompts against a defined task under time constraints. Later rounds typically involve a system design discussion covering evaluation strategy and a behavioral interview assessing how you scope ambiguous problems. Some companies add a portfolio review where you walk through a real prompt chain and explain your design decisions.
Where can I find and apply to prompt engineer jobs?
You can find and apply to prompt engineer jobs on Migrate Mate, which lists current openings from across the United States in one place. Search the listings to find roles that match your skills, specialization, and preferred location or remote arrangement, then apply directly to each one that fits.
See All 13 Prompt Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
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