Sr. Applied Scientist, Applied AI Solutions

Amazon • Seattle, WA

3d • Onsite

About The Position

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.

Are you excited about pushing past single-turn chat into agents that run for hours or days, planning, recovering from failure, and accumulating knowledge as they work? Do you want to design the harnesses, memory systems, and context strategies that turn frontier models into reliablen collaborators on real business problems? Do you enjoy the prospect of solving agent problems that haven't been solved at scale anywhere before, including memory decay, belief revision, fact grounding, long-horizon credit assignment, and evaluation of open-ended trajectories?

Along the way, you'll get opportunities to be a disruptor, innovator, and a problem solver, someone who truly enables AI agents to create significant impacts.

Requirements

• 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

Nice To Haves

• 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.

Responsibilities

• Partner with cross-functional business and engineering teams to identify and deliver high-impact agentic use cases across the Applied AI Solutions portfolio.
• 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.
• 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.
• Set technical direction, mentor scientists and engineers, and represent the science org in roadmap and architecture decisions.
• Ensure seamless deployment and integration of agents into production systems customers rely on daily.

Benefits

• 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
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree