AmazonManager, Software Development, Selling Partner Selection Success
Amazon is hiring a Manager, Software Development, Selling Partner Selection Success in Seattle, United States. It pays $185k-$250k a year and Level rates it ; you can apply on Amazon.
Level's read on this job
- Builds AI ●●●● is how Level rates this role: the job is building AI systems.
- The posting mentions Bedrock, SageMaker and MLOps among its tools and skills.
- Level classes it as a senior role.
- Amazon has 20,000+ other open roles on Level.
- Posted in the last few days.
AI in this role
As a Software Development Manager on our team of scientists and engineers, you will have opportunities to make a significant impact on our systems, our business, and most importantly, our customers. You will lead a team working across a diverse and evolving technology stack, spanning agentic AI and large language model (LLM)-powered systems, machine learning and deep learning models. You will own the end-to-end engineering lifecycle of these solutions, from building intelligent seller-facing experiences to developing scalable ML infrastructure and MLOps capabilities that enable rapid experimentation, reliable model deployment, and efficient production operations.
You will work closely with Applied Scientists, Product Managers, and other engineering teams to translate innovative scientific solutions and ambiguous business needs into scalable, production-ready capabilities. You will drive technical vision, navigate complex engineering challenges across multiple AI/ML paradigms, and foster a culture of invention, operational excellence, and continuous improvement. This role offers a unique opportunity to shape the engineering foundation of next-generation AI-powered seller experiences while building and developing a high-performing engineering team.
Key job responsibilities
- Define and drive the engineering vision and technical strategy for AI/ML-powered solutions across New Selection Success and Seller Growth Recommendations.
- Lead the design, development, and operation of scalable seller-facing applications and services leveraging tech stacks such as agentic AI, LLMs, machine learning, and deep learning.
- Own end-to-end MLOps and AI infrastructure, including model deployment, inference serving, monitoring, and lifecycle management, and partner closely with Applied Scientists to to enable rapid experimentation and efficient delivery of new features.
- Drive engineering excellence and operational best practices to ensure the scalability, reliability, performance, and cost efficiency of production systems.
- Hire, mentor, and develop a high-performing engineering team, fostering a culture of innovation, ownership, and continuous improvement.
- Collaborate with product and business stakeholders to translate ambiguous customer needs into actionable engineering plans and deliver measurable seller and business impact.
Basic qualifications
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
- 3+ years of engineering team management experience
- 7+ years of working directly within engineering teams experience
- 3+ years of designing or architecting (design patterns, reliability and scaling) of new and existing systems experience
- Experience partnering with product or program management teams
Preferred qualifications
- Experience in recruiting, hiring, mentoring/coaching and managing teams of Software Engineers to improve their skills, and make them more effective, product software engineers
- Experience in optimizing production ML systems for scalability, reliability, latency, and cost
- Experience with AWS machine learning services such as SageMaker, Bedrock, or equivalent cloud-based ML platforms
- Demonstrated experience leveraging generative AI tools to enhance workflow efficiency and productivity, with the ability to craft effective prompts and critically evaluate AI-generated outputs in a professional setting
- Experience identifying opportunities to integrate AI solutions into products and services to drive business value
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 - 184,900.00 - 250,200.00 USD annually
How we rate this
Manager, Software Development, Selling Partner Selection Success at Amazon rates 87 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Walk me through how you've used Bedrock in your day-to-day work.
- What are the limits of SageMaker that you've run into, and how did you work around them?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: ML Ops, Bedrock, and SageMaker. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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