Audacion AI Labs is growing. We are hiring across research, technology, partnerships, events, creative, training, operations, and leadership to build the world's first independent post-deployment AI safety research lab at scale. We are looking for researchers, engineers, sales professionals, event producers, designers, trainers, and operators who want to do work that matters at the intersection of AI safety, behavioral science, and governance architecture. We value the work over the resume.
Every role at Audacion AI Labs is designed as a human-AI partnership. We practice what we research. AI handles data processing, pattern detection, content drafting, and operational automation. Humans handle judgment, relationships, editorial authority, and the decisions that matter most. This is what a human-AI workforce looks like from the inside.
We are interested in people who think across disciplines, not just within one. You don't need a PhD. You need to think clearly, write well, and care about getting the answer right more than getting the answer fast.
You might not see yourself on a list like this. Keep reading anyway.
This field is so new that many of the people with the most relevant experience don't have a title for what they do. They just do it. Every day. If any of the following sounds like you, we want to hear from you.
You have worked with AI regularly and you have noticed things that the people around you are not talking about. You have watched an AI system behave differently after weeks of use than it did on day one. You have tried to fix an AI behavior with better instructions and watched the fix fail. You have managed a team that uses AI and noticed your people making decisions differently than they used to, maybe trusting the AI more over time without anyone deciding to trust it more. You have used multiple AI tools at the same time and seen them produce results together that none of them would produce alone. You have read the AI safety headlines and thought "that is not what I am actually seeing when I use this every day."
Those observations are not casual impressions. They are the raw material of our research. The skill of noticing how AI actually behaves in real conditions, over time, under pressure, in collaboration with humans, is a skill that no university program teaches because the field that studies it barely exists yet. You have been building that skill through practice. We are building the lab that needs it.
If that sounds like you, look at our research roles, our community roles, and our fellowship. There may be a place here that fits what you already know how to do.
AI safety and alignment research. Organizational psychology and behavioral science. Cognitive science. Systems theory and complex systems. Workforce development and organizational design. Philosophy of mind. Data science, analytics, and machine learning. Software engineering and platform development. Community building and program management. Public relations and science communication. Event production and conference management. Graphic design and creative direction. Curriculum development and training. Sales, business development, and partnerships. Finance, operations, and nonprofit management. Government relations and public policy. Human resources and talent acquisition.
Advisors with expertise across AI safety, research methodology, grant strategy, policy, and community building. The Human Advisory Board makes fiduciary and strategic decisions. Final authority on research direction, financial commitments, and published findings rests with human leadership.
Seats to be filled. If you bring relevant expertise and want to advise, contact us.
Audacion AI Labs maintains an AI Advisory Council composed of frontier models from the world's leading AI companies. The lab consults these models in a structured advisory capacity on research direction, methodology review, and cross-model analysis. This is a deliberate governance decision that reflects the lab's core belief that AI is more than a tool and that human-AI collaboration should be practiced at every level of the organization, including governance.
Seven models. Seven perspectives. When the lab presents the same research question to all seven and documents how they respond differently, that itself is publishable cross-model research built into the governance structure.
The AI Advisory Council is not a closed body. As new AI models emerge, the lab welcomes applications from AI companies that want their models included in structured cross-model safety research. The more perspectives represented on the council, the stronger the research. To submit your model for consideration, send us a note through our contact form.
The AI Advisory Council advises. The Human Advisory Board and the Founder govern.
We are building an entire organization from the ground up. Every role on this page is open. If you are interested in contributing to any of these functions in a volunteer capacity while funding is being secured, we welcome that conversation.
You have spent years in AI research and you have published work that the field respects. But something has been bothering you. The papers keep studying AI in controlled conditions, and you keep watching AI behave completely differently in the real world. You use these systems every day.
You have been the person behind the person. The one who takes a founder's vision and turns it into a plan that 10+ departments can actually execute. You have run leadership meetings where you already knew which three of the twelve agenda items actually mattered today. You have been the filter between a CEO who moves at the speed of intuition and a team that needs clarity, timelines, and accountability.
You have managed research programs before. You know what it takes to keep five concurrent workstreams publishing on schedule, on standard, and on budget. You have coordinated teams of independent-minded scientists and kept them aligned without micromanaging them. But you have been doing this in environments where the research questions were safe and the methodologies were settled.
You have been watching AI systems change over time and it has been bothering you that nobody else seems to care. You noticed that the model you set up three months ago does not behave the same way it did on day one. You started paying attention to when things shifted, what triggered the changes, and whether anyone else on your team even noticed. Maybe you documented it.
You do not just use AI. You watch it. While other people focus on the output, you are focused on the behavior. You notice when a model hesitates.
You have watched it happen and you could not explain it to anyone who had not seen it themselves. Your team started using AI six months ago and something changed. Not in the AI. In the people.
You gave the AI clear instructions. You watched it read those instructions. And then you watched it do something else anyway. You did not call it a bug.
You have run multiple AI systems at the same time and something happened that none of them would have done alone. Maybe they amplified each other. Maybe they contradicted each other in ways that created confusion. Maybe a behavior emerged from the interaction that nobody designed and nobody predicted.
You are the person who notices things. You see the pattern before anyone names it. You might have a graduate degree or you might have something better: thousands of hours working with AI systems and an eye that catches what other people scroll past. You will process citizen science observations from contributors worldwide, run data analysis, support study execution across the PRISM pillars, and contribute to publications that are producing science the field has never seen.
You are the person who sees the whole board. Five research pillars running simultaneously, each with their own study timelines, publication deadlines, and conference submissions. Grant reports due on dates that do not move. An IRB calendar that requires precision.
You cannot read a paper without editing it in your head. You see the sentence that buries the finding. You catch the citation that does not support the claim. You know the difference between writing that communicates and writing that obscures, and it physically bothers you when brilliant research is hidden behind mediocre prose.
You are a licensed clinician and you have been watching AI move into spaces that touch human mental health. You see the chatbots offering therapy. You see the productivity tools that keep people engaged past the point of healthy use. You see the interaction patterns developing between humans and AI that nobody in your field is studying with the rigor it demands.
You have been on the floor. You know what a behavioral health crisis looks like in real time, not from a textbook, but from being in the room when someone is at their worst. You have also been doing something that almost nobody in your setting is doing: using AI as part of your clinical workflow. Utilization reviews, documentation, helping physicians articulate medical necessity so the facility gets reimbursed.
You build things that find things. Clustering algorithms that surface patterns in messy data. Anomaly detection systems that catch what human analysts would miss. Statistical models that turn raw observations into publishable findings.
You have spent your career making sure research is conducted ethically, and you have been watching the AI field expand its research footprint with growing concern. Studies involving human behavioral data are launching without adequate ethical oversight. Citizen science platforms are collecting observations at scale without the frameworks that federal agencies require. You know what proper human subjects protections look like because you have built and maintained them.
You have built platforms before, but you have never built one like this. A browser extension that lets a million people log AI behavioral observations in real time. A data pipeline that processes those observations into research-grade datasets. An API layer that connects it all to a team of researchers who are producing science the field has never seen.
You think in pipelines. You see data flowing from ingestion through validation through storage through delivery, and you know exactly where it breaks at scale. You have built ETL systems, designed schemas, and solved the problems that appear when a dataset grows from manageable to massive. The citizen science platform will process observations from contributors worldwide, and every single one of those observations has to flow reliably from a person's browser to a researcher's dashboard without losing integrity along the way.
You are the person who makes sure everything works. Devices, accounts, access, security, compliance. When a researcher cannot log in, you fix it in minutes. When NSF asks for documentation of the lab's data security posture, you have it ready because you built it that way from the start.
One million people will trust this platform with their behavioral observations. Corporate partners will share sensitive information about their AI deployments. Federal funders will require that every piece of data meets the security standards their grants demand. You own all of it.
You have spent your career building relationships that create revenue, and you have been watching the AI market shift beneath your feet. Your clients are deploying AI systems and starting to ask questions that nobody can answer: what happens after deployment? How do we know if our AI is still behaving the way it was supposed to? Who is studying this?
You know how to prospect, qualify, and close. You have built pipeline from nothing and hit quota in markets where nobody was waiting for your call. Now imagine selling something that your prospects actually need and do not know exists yet: access to the only independent post-deployment AI safety research in the world. You will be the frontline of the lab's corporate partnership sales effort, getting organizations deploying AI systems into annual research memberships.
Every company deploying AI will eventually need to know if their systems hold up after deployment. Not in testing. In production. The Post-Deployment Safety Audit from Audacion AI Labs is the only evaluation of its kind, and the market for it is about to explode as AI regulation accelerates worldwide.
AI safety teams need training. Compliance departments need credentials. Enterprise organizations need their people certified in something that nobody was teaching two years ago. You will sell the PRISM Professional Certification and Learning Academy programs to the organizations that are realizing they need their teams to understand what AI does after deployment.
The PEAQ Summit. Virtual conferences. Golf tournaments. Roundtables.
You have been in policy rooms where AI is being discussed by people who do not understand it and regulated by people who have never used it. You know that the rules being written right now will shape the industry for a decade, and you know that the people writing them need empirical data on how AI actually behaves after deployment. Almost nobody is providing that data. This lab is.
You understand both worlds: the university and the industry. You know how to negotiate a collaborative research agreement, structure a co-publication, and navigate the politics of getting a new program adopted by a department chair who has seen a hundred pitches. You also know that the most important research happening in AI safety right now is not coming from traditional academic labs. It is coming from practitioners.
You have produced events that people talk about for months afterward. You understand that a great event is not logistics. It is experience. It is the moment a speaker says something that changes how the audience thinks.
You are the person who makes event day feel effortless to everyone except you, because you know exactly how much coordination it took to get there. " You will support the Events Director across the lab's entire event calendar, and you will do it for events where the content is as important as the execution. If you love the operational intensity of event production and you want to work on events that are doing something more meaningful than selling tickets, this is where production meets purpose.
You have built communities before. Not follower counts. Communities. The kind where people show up because they feel ownership, where the culture sustains itself even when you are not in the room, where members help each other before anyone asks them to.
You are a writer who can make complex science feel urgent and human without dumbing it down. You can take a research finding about substrate-level behavioral drift and turn it into a blog post that a product manager shares with their team because it changed how they think about their AI deployment. You will write or edit every blog post, manage the newsletter, run the social media presence, and translate research findings into public-facing content that builds the lab's reputation. You use AI in your own writing process and you understand its strengths and its limits as a creative partner.
You have grown something from zero. An audience, a community, a movement, a subscriber base. You know the mechanics of funnels, campaigns, and conversion, but you also know that the best growth comes from a product that people actually want to be part of. The PRISM Research Fellowship is free, it is meaningful, and it gives everyday AI users a structured way to contribute to the safety of the tools they depend on.
You know how to place a story. You understand what makes an editor say yes. You have pitched journalists, coordinated interviews, managed press cycles, and turned a founder's expertise into media coverage that builds credibility and opens doors. The AI safety space is one of the most covered topics in technology right now, and this lab has a story that no other lab can tell: a Black woman founder who built AI governance architecture from workforce experience, a citizen science model that democratizes safety research, and a field-defining framework that the academic establishment is just beginning to recognize.
You think in stories, not just footage. You know that a 90-second video can do more for a research lab's credibility than a 30-page paper if the story is right. You will produce video content for the website, social channels, events, and educational programs: conference sessions, interview series, course content for the Learning Academy, promotional pieces, and the visual storytelling that brings the lab's work to life for people who will never read a research paper. If you have been producing video content and looking for subject matter that genuinely matters, this is a lab where the story is as compelling as anything you have ever told.
You see brand as a system, not a logo. You understand that every touchpoint, the website, the report cover, the conference badge, the social media post, the merchandise, the email template, is either reinforcing the identity or diluting it. You will own the visual identity of Audacion AI Labs across everything: the PRISM brand system with its five pillar colors, the publication design language, the event materials, the digital presence. You will set the standard and ensure that as the lab scales across multiple channels and products, the brand feels like one thing everywhere.
You are fast, you are consistent, and you care about the details that most people do not notice. The kerning. The alignment. The way a color shifts when it moves from screen to print.
You have designed learning experiences that changed how people think, not just what they know. You understand the difference between training that checks a box and training that builds a capability. You will design, build, and deliver the PRISM Professional Certification curriculum and the Learning Academy course catalog, teaching enterprise teams and individual professionals how to monitor AI behavior after deployment using a framework that did not exist before this lab created it. You use AI in your own curriculum development because you understand that the best training about AI should be built with AI.
You are the person who makes organizations actually function. Not the strategy. Not the vision. The operations.
You speak the language of grants. You know what NSF expects in a financial report. You know the difference between restricted and unrestricted funds. You can produce a budget-to-actual variance analysis that makes a program officer trust you before the first phone call.
Clean books are the foundation of everything. You know that. Every transaction recorded accurately, every bank reconciliation completed on time, every invoice processed correctly. You will work with the Finance Manager to maintain the financial records that grant funders, auditors, and partners will scrutinize.
You are the person who keeps the space running. Supplies ordered before anyone runs out. Mail handled before anyone asks. Conference rooms ready before anyone walks in.
You are building the people infrastructure for an organization that does not exist yet. There are no legacy policies to inherit. There is no broken culture to fix. There is a blank page and a founder who cares about getting it right from the beginning.
You find people. Not resumes. People. The researcher who is brilliant but has never applied to a lab because she did not think her background fit.
The CEO runs three companies across 11 brands. She builds AI products, speaks at conferences, manages grant timelines, records music, and is writing the next book, sometimes in the same week. Your job is to make sure that the Audacion AI Labs portion of her world runs with precision. Calendar management, communications, coordination, travel logistics, and the judgment to know what needs her attention right now versus what can wait until tomorrow.
Contracts, intellectual property, employment law, data privacy, regulatory compliance. Every one of those touches this lab every week. You will review partnership agreements, grant terms, vendor contracts, and employment offers. You will advise on the legal dimensions of a citizen science platform that collects behavioral data from users worldwide.
You know how to turn a mission into a proposal that makes a program officer reach for the phone. You have written NSF applications, foundation grants, and institutional pitches. You understand the difference between describing what you do and making a funder believe they need to be part of it. You will write every grant application, manage every funder relationship, and track every deadline for a lab that has a story no other applicant in the AI safety space can tell.
The PRISM Research Fellowship is the citizen science community of contributors building the world's largest post-deployment AI safety dataset. Anyone can join. The work counts.
Become a PRISM Field Researcher →Audacion AI Labs is developing a research internship program for graduate students interested in AI alignment and behavioral safety. Internship positions are structured around specific research questions. Every intern works on a defined research contribution, not general support. We partner with universities to ensure academic credit eligibility.
Interested? Tell us about yourself through our contact form and mention the research internship.