The AWS Marketplace & Partner Services (AMPS) Science team seeks a Software Engineer to design and build the infrastructure and tooling behind our AI solutions, including LLM training pipelines, custom LLM model hosting, and AI agent monitoring and evaluation infrastructure. This role will be instrumental in transforming how AMPS customers and partners interact with our AI-powered products, including AMPS AI agents. In this role, you will work closely with Data Scientists, Applied Scientists, Data Engineers, other Software Engineers, Business Intelligence Engineers, Product Managers, and AMPS managers and leaders to build and scale the infrastructure and tooling that power our AI solutions.
The ideal candidate thrives in an environment of practical application, demonstrating both technical excellence and business acumen. They should be passionate about collaboration and contributing to a culture of continuous learning and innovation. This role directly influences how thousands of AWS customers and partners as well as internal users and systems work, making it crucial for AWS Marketplace's growth and customer success. The position offers the opportunity to shape the future of AI-driven solutions while working with innovative technologies at AWS scale.
Key job responsibilities
- Design, develop, and maintain scalable infrastructure for large language model training pipelines, model hosting, and agent-based systems, employing best engineering practices and iterating from simple to complex solutions
- Build and operate monitoring, evaluation, and observability frameworks to measure AI agent performance, reliability, and effectiveness in production
- Develop reusable tooling, APIs, and automation that accelerate the team's ability to experiment, deploy, and iterate on ML/AI solutions
- Contribute to a fast-paced, experimental environment by rapidly prototyping and operationalizing infrastructure that leverages the most recent advances in ML/AI
- Collaborate with cross-functional teams—including Data Scientists, Applied Scientists, Data Engineers, Software Engineers, Product Managers, and Science and Engineering leaders—to translate scientific innovations into robust, production systems
- Participate in research initiatives alongside scientists and engineers—contributing to experiments, prototyping, and co-authoring internal and external publications that advance the team's technical knowledge and industry presence.
A day in the life We are at the forefront of developing and deploying AI/ML systems that serve multiple critical stakeholders:
- AWS Customers: Through the AWS Marketplace, we build and support Discovery tools and AI agents that streamline cloud adoption and innovation.
- AWS Partners: Via Partner Central, we offer advanced tools and insights to enhance collaboration and drive mutual growth.
- Internal AWS Sellers: We equip our sales force with data-driven recommendations and AI tools to better serve our customers and partners.
- Our primary objective is to accelerate cloud migrations and modernizations, fostering innovation for AWS customers while simultaneously supporting the growth and success of our extensive partner network.
About the team AMPS' vision is to make AWS the most efficient, automated, and economical place for customers worldwide to find, buy, and deploy third-party software, data, and professional services. The AMPS Analytics and Science Engineering Team drives innovation through data science, machine learning research, and rigorous AI evaluation. We partner with other AMPS teams to improve discovery, recommendation, AI systems performance and evaluations, and partner success across AWS Marketplace.
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.
Basic Qualifications
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
- 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
- 2+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services
- 2+ years of experience working with cloud services (e.g., AWS, Azure, GCP).
Preferred Qualifications
- Master's degree or equivalent
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Knowledge of machine learning methodologies and experience with agentic AI systems, and related frameworks and SDKs (e.g., LangChain, LangGraph, Amazon Bedrock Agents, Claude), with hands-on experience building, deploying, and maintaining infrastructure for AI-powered systems in production environments.
- Experience with building infrastructure for LLM fine-tuning pipelines and model hosting services—including training orchestration, model versioning, deployment automation, and cost-efficient serving at scale.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including 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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle - 143,700.00 - 194,400.00 USD annually