Sr. Principal Scientist, Kiro Science

Description

We are building the systems foundations for the next generation of autonomous coding agents, agents that operate in parallel, run for hours or days, and collaborate on codebases at a scale that breaks the assumptions of tools built for human developers. The hard problems in this space are no longer about model quality alone. They are about the systems layer underneath: how agents coordinate, how state is managed across long horizons, how correctness is preserved when many agents act concurrently, and how deterministic infrastructure can take on responsibilities that LLMs cannot reliably handle.

Our team treats these as first-class research and engineering problems. We are designing new primitives for coordination, concurrency control, state management, validation, and inter-agent communication that move responsibility out of fragile LLM-mediated paths and into systems that are predictable, debuggable, and fast. Early prototypes have produced order-of-magnitude improvements in throughput and eliminated entire classes of integration-time failures that conventional architectures ship silently.

The opportunity ahead is to define what the standard agent-systems stack looks like.

Key job responsibilities

Key job responsibilities

- Develop breakthroughs in agentic architecture across areas such as autonomy, self-validation, continuous learning and time series foundation models.

- Mentor and guide junior scientists.

- Develop technology strategy and roadmap supporting product development

- Develop prototypes for key technology, oversee the productization of the prototype, and develop critical assessment for the prototype

- Write technical reports summarizing R&D progresses and communicate such progresses with stakeholders

Basic Qualifications

- PhD, or Master's degree in CS, CE, ML or related field experience

- Experience programming in Java, C++, Python or related language

- Experience in any of the following areas: AI (NLP or multi-modality models), Deep Learning, LLM model training, graph learning, software engineering.

Preferred Qualifications

- 15+ years of relevant, broad research experience after PhD degree or equivalent.

- First author publications at Tier-1 ML conferences such as NeurIPS, ICLR, ICML, CVPR.

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

Los Angeles County applicants:
Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position.

These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company's reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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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   .

USA, CA, Santa Clara -  -  USD annually

USA, WA, Seattle -  -  USD annually