About the job
The newest business group in AWS, Applied AI Solutions are built by AWS and AWS Partners to deliver applied AI solutions that leverage Amazon's operational expertise and that businesses love and trust for their day-to-day success. Our ambition is to become a partner which companies can rely on to run their business every day, putting AI to work delivering better customer experience, operational excellence and speed.
Responsibilities
You will partner with cross-functional business and engineering teams to identify and deliver high-impact agentic use cases across the Applied AI Solutions portfolio. You will design, develop, and evaluate long-running agents — including orchestration harnesses, memory architectures (episodic recall, semantic facts, revisable beliefs, principled decay), context compaction strategies, and safe, auditable tool and environment designs.
You will define evaluation frameworks for agents whose outputs defy single-answer judgment, building trajectory-level evaluations, reward-hacking detection, and human-in-the-loop review patterns. As a senior scientist, you will set technical direction, mentor scientists and engineers, and represent the science org in roadmap and architecture decisions.
You will ensure seamless deployment and integration of agents into production systems customers rely on daily.
Qualifications
Minimum
3+ years of building machine learning models for business application experience
Experience programming in Java, C++, Python or related language
Experience with neural deep learning methods and machine learning
5+ years of applied research experience
PhD in CS (Computer Science), CE (Computer Engineering), or related technical field, OR MSc + 10 years, OR BSc + 12 years
Preferred
Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
Experience with large scale distributed systems such as Hadoop, Spark etc.