Sr. Applied Scientist - Agentic AI, Amazon Connect

Amazon is hiring a Sr. Applied Scientist - Agentic AI, Amazon Connect in Seattle, United States. It pays $167k-$226k a year and Level rates it ; you can apply on Level.

Level's read on this job

Level rates this applied scientist role Builds AI ●●●●: the job is building AI systems.
Pay on this posting starts in line with the typical applied scientist posting on Level.
The posting mentions Bedrock, vLLM and PyTorch among its tools and skills.
Amazon has 22,000+ other open roles on Level.
This posting went up in the last few days.

AI in this role

bedrockvllmpytorchsagemaker

fine-tuning

Do you want to join a team of innovative scientists to research and develop Agentic AI technology that would disrupt the industry? Do you enjoy dealing with ambiguity and working on hard problems in a fast-paced environment? Amazon Connect is an AI-first customer experience solution that enables superior outcomes at a lower cost. Since its 2017 public launch Amazon Connect has become an AI leader transforming how organizations of all types interact with their customers.

As a Sr. Applied Scientist on our team, you will work closely with senior technical and business leaders from within the team and across AWS. You distill insight from huge data sets, conduct cutting-edge research, and develop science solutions to conquer complex business problems, from conception to deployment. You own the measurement science behind your work — defining the offline evaluation harnesses and online experiments that prove an agentic system is actually better, and converging on a small number of trustworthy metrics that tie model quality to customer outcomes. You have a strong academic background and industry experience in machine learning and deep learning, with deep domain knowledge in generative AI and LLMs. You are comfortable quickly prototyping and iterating on your ideas to build and evaluate robust agentic systems using modern tooling such as PyTorch, vLLM, agent frameworks and MCP, and AWS services including Amazon Bedrock and SageMaker.

Learn more about Amazon Connect here: https://aws.amazon.com/connect/

About the team
Our team is leading AI/ML research and development in Amazon Connect. We use state-of-the-art science and engineering practices to address the hard problems in contact center for our customers, and we move fast to implement solutions and refine them based on customer feedback.

Basic qualifications

- 5+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Demonstrated experience with generative AI and LLMs — fine-tuning, prompting, retrieval, or post-training.

Preferred qualifications

- PhD, or a PhD or equivalent research experience and experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience in automation or monitoring frameworks, deployment or development
- Experience designing evaluation frameworks for open-ended or subjective tasks where ground truth is expensive or unavailable, including synthetic data generation.
- Experience with agentic and multi-turn systems, including RL-based post-training (RLHF/RLAIF/GRPO or similar), environment simulation, or agent harness evaluation.

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, WA, Seattle - 167,100.00 - 226,100.00 USD annually

How we rate this

Sr. Applied Scientist - Agentic AI, Amazon Connect at Amazon rates 97 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

Sr. Applied Scientist - Agentic AI, Amazon Connect is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $167k-$226k a year.
The role is based in US, WA, Seattle.
The job was posted on October 16, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Fine-tuningBedrockvLLMPyTorchSagemaker

Also common in applied scientist jobs at this level

NLP TensorFlow Spark Computer vision scikit-learn AI agents

Pay

This job starts at: $167k
Typical applied scientist job: $167k

This posting starts close to the typical applied scientist job. See applied scientist jobs

Questions you could be asked

Walk me through fine-tuning a model: what data did you use, and how did you check the result?
Walk me through how you've used Bedrock in your day-to-day work.
What are the limits of vLLM that you've run into, and how did you work around them?
What's a project where you used PyTorch hands-on?
Walk me through how you've used Sagemaker in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Fine-tuning, Bedrock, vLLM, PyTorch, and Sagemaker. 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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