Principal Data Scientist, Agentic AI Professional Services

Principal Data Scientist

AWS is seeking an exceptional Principal Data Scientist to join our Agentic AI ProServe Experience (APEX) team. This role calls for an individual ready to tackle large-scale agentic AI challenges and drive innovative ML/AI practices that transform professional services delivery and address real-world customer needs. Reporting directly to the leader of APEX, this position is essential for revolutionizing AWS Professional Services' delivery capabilities through advanced agent-based AI systems. In addition to building ProServe Agents, you will driving their adoption across the ProServe builder community, enabling transformative customer engagements and partner enablement through AWS tools and services such as Kiro, AWS Transform, Strands, Bedrock, and Agentcore. The ideal candidate will possess extensive experience in agentic AI systems, multi-agent architectures, and complex data science environments, developing solutions that advance the state-of-the-art in agent-based professional services delivery. Proficiency with Machine Learning, Large Language Models, reinforcement learning, and advanced analytics techniques is essential, along with the ability to convey these technical concepts in simple terms to diverse stakeholders. The role demands both deep technical expertise and exceptional communication skills to drive adoption across the ProServe organization and partner ecosystem.

Key Job Responsibilities

Scientific Leadership

• Define and drive the scientific vision and roadmap for ProServe Agents and the agentic AI professional services portfolio
• Lead research and development initiatives to advance the state-of-the-art in agent-based AI systems for professional services workflows
• Collaborate with senior scientists across AWS to pioneer novel approaches to agent learning, reasoning, and interaction
• Publish innovative research at top-tier conferences and influence the broader scientific community
• Evaluate emerging research and identify opportunities to integrate techniques into ProServe Agent architecture

Technical Excellence

• Architect complex multi-agent systems that can effectively understand, reason about, and execute professional services workflows at enterprise scale
• Lead the integration of Gen AI and ML-based methods across ProServe delivery practices, spearheading AI-driven agent development and adoption initiatives
• Establish rigorous evaluation frameworks and metrics for measuring agent effectiveness, safety, and business impact
• Develop production-ready agentic solutions leveraging AWS tools including Kiro, AWS Transform, Strands, Bedrock, and Bedrock AgentCore

Customer & Business Impact

• Translate complex technical concepts into clear business value propositions for ProServe builders, customers, and partners
• Lead high-visibility technical delivery for strategic customers, demonstrating ProServe Agent capabilities
• Drive adoption of ProServe Agents across the AWS Professional Services builder community, transforming delivery methodologies
• Enable AWS partners on agentic delivery mechanisms and best practices
• Analyze complex enterprise problems and design AI agent solutions that deliver measurable business outcomes
• Collaborate effectively with ProServe delivery teams, product, engineering, and design teams to create and launch innovative agent-based solutions

Leadership & Mentorship

• Provide thought leadership and technical direction on agentic AI strategies and their applications in professional services
• Drive innovation by sharing new technical solutions and product ideas across AWS teams
• Mentor and guide the data science, ML engineering, and ProServe builder communities
• Foster collaboration with key stakeholders to enhance the AWS ProServe experience

Basic Qualifications

Master's degree in Math, Statistics, Computer Science, or related Science field, or experience in data science, machine learning or data mining

Experience building machine learning models or developing algorithms for business application

Preferred Qualifications

8+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience

4+ years of practical machine learning experience

2+ years of working with or evaluating AI systems experience

Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience debugging, profiling, and implementing best software engineering practices in large-scale systems

Experience with one of the following areas: machine learning technologies, Reinforcement Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP) or related applications

Have publications at top-tier peer-reviewed conferences or journals

Experience with AWS or cloud technologies

Experience in technical leadership of development, testing, and implementation of large-scale, complex technology projects

Experience driving collaborative projects from conception to delivery, or experience in development or technical support

Experience creating and delivering written and oral communications for technical and non-technical audiences