Humorphic Labs builds AI systems that work as teammates rather than tools, and ships them six months or more ahead of anyone else. The Lab is small on purpose, so it can change direction in a day.
Humorphism is the quality of the working relationship between a person and an AI system. It asks whether the system acts proactively, adapts to the person and the situation, earns trust, manages attention, and strengthens human judgment. The work is closing the distance between a tool a person operates and a teammate a person collaborates with.
You will start in the Lab and build a capability that does not exist yet. Then you will deploy into the Applied AI Solutions product team that carries it, and stay until that product ships it and customers use it. Adoption is yours. Over time the same pattern extends to AWS service teams.
The Lab does not run production at scale. Once a capability proves itself, architecture and scaling move to the product team, and you return with what you learned.
There is no fixed technology stack. The work leans toward the web frontend, because a teammate is judged on the surface where a person meets it, and extends to native mobile, voice, and other modalities as the problem demands. Some of these problems have no known solution today. Multimodality is one.
The Lab is a lead who still writes code, an Applied Scientist, and engineers. Applied AI Solutions leadership approved it with one instruction - to explore the limits of what we can build - and one number: to ship six or more months ahead of what others can do.
The Applied Scientist owns the hypotheses and the evaluation. You build the systems that test them and the products that carry the ones that survive.
We have a sunset clause. Once a capability is proven and integrated into its product, the Lab moves to the next frontier.
Key job responsibilities
- Build AI teammate capabilities in the Lab, from a thesis to a working product, in line with the Humorphism design philosophy and with guidance from the Lab lead and the Applied Scientist.
- Implement the experiments the Applied Scientist designs, and turn research results into working software.
- Deploy into a product team, work alongside them, and drive your capability into their product.
- Own adoption of what you build. Measure it, report it, and stay until customers use it.
- Identify where the work breaks down in a host team's hands, then correct the cause rather than the symptom.
- Partner with UX designers, product teams, and other organizations to deliver complete humorphic experiences.
- Transfer architecture and scaling to the product team at the agreed boundary, with the documentation and tests that make the transfer safe.
- Contribute your work back into the shared humorphic layer, so the next capability starts from a higher floor.
- Learn unfamiliar languages, runtimes, and problem domains as the work requires.
- Write tested code, review the code of others, and operate what the Lab runs.
- Present the work to the host team, the Lab, and SCORE, and participate in internal reviews.
A day in the life
Your calendar has two shapes.
In a Lab week you write code most of the day. You take a thesis about how a teammate should behave, build the smallest version that tests it, and put it in front of a person before the week ends. You sit with a UX designer to work out how the behavior should feel, not only what it does.
In a deployed week you sit with the product team carrying your capability. You watch a real user hit the seam between your work and theirs, and you fix it that afternoon. Expect occasional travel.
About the team
BASIC QUALIFICATIONS
- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language
- Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Experience building complex software systems that have been successfully delivered to customers
PREFERRED QUALIFICATIONS
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
- Experience building with large language models or agent frameworks in a product rather than a demo
- Experience learning an unfamiliar language or runtime to solve a problem, then shipping in it
- Experience embedded in another team, with responsibility for whether that team adopted your work
- Experience building native mobile applications
- Experience with multimodal input or output, such as audio, video, voice, or gesture
- Experience partnering with design, product, and behavioral research from problem definition through product validation
- Experience with interaction craft: motion, timing, and feedback that make software feel responsive
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, TX, Austin - 143,700.00 - 194,400.00 USD annually
