AmazonPosted 1w ago

Software Development Engineer, Humorphic Labs

Software Development Engineer, Humorphic Labs at Amazon scores 90 out of 100 on AI centrality, which makes it a Level 4 role on this board.

US, TX, Austinseniorfull-time$144k-$194k

AI in this role

Build innovative AI teammates and human-AI interaction systems ahead of industry standards.

reactreact-native

software-developmentfront-endmultimodalityai-systems

As part of the AWS Applied AI Solutions organization, we have a vision to provide business applications, leveraging Amazon’s unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers’ businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon’s real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use.

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
ABOUT AWS:
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity and AmazeCon conferences, inspire us to never stop embracing our uniqueness.

Mentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

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

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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

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A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Software DevelopmentFront EndMultimodalityAI SystemsReactReact Native

Questions you could be asked

Tell me about a project where software development was part of your work. What did you do?
Tell me about a project where front end was part of your work. What did you do?
Tell me about a project where multimodality was part of your work. What did you do?
Tell me about a project where ai systems was part of your work. What did you do?
Walk me through how you've used React in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Software Development, Front End, Multimodality, AI Systems, and React. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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