Software Development Engineer, Conversational AI Modeling and Learning, Full-time

The Alexa Conversational AI Modeling and Learning (CAMEL) team is looking for a highly-skilled SDE to lead a new initiative which is at the forefront of using state of the art (SOTA) innovations in Large Language Models (LLMs) to build an AI agent which can converse naturally with customers, entertain them, perform their requested tasks and act autonomously to solve complex tasks.

As an SDE on the team, you will own building and re-architect tier-1 services which are responsible for end-to-end orchestration and execution of multi-modal conversational agent requests. From getting the best prompt and context for the request, to picking the correct model to inference, to interpreting LLM’s output, creating an actionable plan and executing it.

We are looking for world-class software developers who like to deliver software solutions that solve business problems and delight your customers with efficiency and productivity gains. You have development experience with technologies like AWS, Java, TypeScript, CDK and LLMs.

Key job responsibilities

– Ability to quickly learn SOTA technologies and algorithms in the field of Generative AI on greenfield projects to participate in our journey to build the best conversational agent.

– Responsible for the development and maintenance of key platforms needed for connecting LLMs to actual user requests and real world APIs which act on them required for building conversational agents.

– Work with other team members to investigate design approaches, prototype new technology and evaluate technical feasibility.

– Work closely with Applied scientists to handle myriad of conversational use cases along with optimizing latency, cost and capacity.

– Work in an Agile/Scrum environment to deliver high quality software in a fast-paced environment.

A day in the life

As a SDE on the CAMEL team, you will be responsible for leading the development of high performance, low latency and low cost solutions for building the best in class conversational agent which solves real world problems for millions of customer. You will have significant influence on our overall strategy by helping define the architecture of tomorrow, where multiple LLMs with different modalities come together to solve real world customer problems. Your work will directly impact our customers in the form of products and services that make use of conversational agent innovations. You will partner closely with experienced engineers and scientists to drive the system architecture, and spearhead the best practices that enable a quality infrastructure.

You’ll start your day connecting with team members to discuss ongoing projects and align on priorities. You might spend time analyzing system performance, implementing new dialogue features, or working with researchers to integrate the latest AI advances. You’ll participate in design reviews, mentor colleagues, and contribute to technical discussions that shape our product roadmap.

About the team

We are a diverse group of engineers, researchers, and scientists passionate about making technology more accessible through natural conversation. Our team values creativity, continuous learning, and supportive collaboration. We encourage experimentation and celebrate both successes and learning opportunities.

BASIC QUALIFICATIONS

– 3+ years of non-internship professional software development experience

– 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience

– Experience programming with at least one software programming language

– Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations

PREFERRED QUALIFICATIONS

– 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience

– Bachelor’s degree in computer science or equivalent

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