Principal Engineer, Connect Analytics

Description

Amazon Connect is a highly disruptive cloud-based contact center that enables businesses to deliver engaging, dynamic, and personal customer service experiences. As a Principal Engineer in Amazon Connect Analytics, you would define a technical strategy and roadmap spanning multiple teams to evolve Analytics towards the Agentic future. You will influence senior management to take goals and investments to achieve that strategy and drive a team of 60+ engineers to architect and deliver on that strategy for the next 2-3 years.

As a Principal Engineer in Connect Analytics, you would be responsible for driving north star technical direction and provide technical leadership across 20+ projects in the Analytics space. Specifically, you would be guiding delivery and operational excellence for a team of 60+ engineers across 6 different 2‑pizza teams and 12 services within the Analytics org which are leveraged for providing standardized out‑of‑the‑box experiences to more than 10,000 Connect customers using them daily to operate their Contact Center business  context, Analytics services and customer experiences (Public APIs, dashboards and zero eTL datalake) enable faster adoption of core Connect offerings (Omnichannel and routing capabilities) as well as enable approximately 35MM ARR in additional paid offerings (Contact Lens, Agent Evaluation, Agent Scheduling and Forecasting) through out‑of‑the‑box Analytics capabilities.

Moreover, you would be leading the charge for transforming Analytics experiences to be "GenAI first", and own the futuristic architecture that supports large‑scale MCP and AI tooling capabilities across heterogeneous data patterns, leading through a team or senior engineers.

While doing that, you will specifically integrate Analytics platforms with AI/ML systems, GenAI capabilities, Rules and Task Management and Agent Orchestration and Observability platforms to evolve Analytics from being a table‑stakes offering to a value generator for Connect.

This role will be working together with 15+ teams spanning across Connect on Analytics related use cases and closely partnering with other AI&O PEs to architect technical solutions that enable standard patterns and experiences solving towards the Self‑Service Contact Center vision across multiple use cases.

In the next 2-3 years, apart from being a technical bar‑raiser on architecture and design across all our key initiatives and operational excellence, this role will work across other PEs in Connect and specifically focus on
1) Driving technical strategy for Generative AI experiences leveraging and integrating with existing platforms, to solve for Analytics specific use cases
2) Driving Data Strategy for Connect as the overarching Technical Lead across teams inside and outside of Analytics org for integrating data from AI/ML, Gen AI, Rules and self‑service capabilities and
3) Evolving Connect zero eTL Data Lake to be a managed service that serves as the backbone for Analytics Knowledge systems for historical context.

Amazon Connect is a highly disruptive cloud-based contact center that enables businesses to deliver engaging, dynamic, and personal customer service experiences. Amazon Connect is the result of the ten years of development that went into building the tools Amazon uses to provide its award‑winning customer service at massive scale and launching it as a publicly available AWS service. With Amazon Connect, you can create your own cloud‑based contact center and be taking calls in minutes.

Amazon Connect leverages the power of Artificial Intelligence and the large ecosystem of AWS services such as Amazon Lex, Amazon Polly, AWS Lambda, Amazon S3 and Amazon Kinesis to provide a truly frustration‑free, easy‑to‑use, extensible, and natural customer experience.

• 12+ years of professional software development experience
• 7+ years of programming experience with at least one software programming language
• 5+ years of experience contributing to the system design or architecture (architecture, design patterns, reliability and scaling) of new and current systems
• Exper…