AmazonSoftware Development Manager, AWS SageMaker
AI in this role
Lead the software engineering team building the AWS SageMaker model customization platform for fine-tuning foundation models.
As the founding engineering leader for this platform, you will own the end-to-end technical strategy, hire and develop a high-performing team, and deliver a scalable, reliable service that operates at Amazon
scale. You will work closely with applied scientists, product managers, and partner engineering teams to define the roadmap and ship features that directly impact customers.
Key job responsibilities
Key Responsibilities
- Build and lead the team: Recruit, hire, mentor, and retain a team of software engineers and machine learning engineers. Establish engineering culture, development practices, and operational standards from the ground up.
- Own the platform: Drive the technical vision and architecture for model customization platform, encompassing model fine-tuning workflows (SFT, RLHF, LoRA, etc.), training orchestration, data processing pipelines, and model
evaluation infrastructure.
- Deliver at scale: Ship production services that handle large-scale distributed training jobs, manage GPU/accelerator resources efficiently, and meet strict availability and latency SLAs.
- Operational excellence: Establish and maintain a high operational bar — define metrics, alarms, runbooks, and on-call processes. Own the operational health of the platform end to end.
- Collaborate cross-functionally: Partner with applied science teams on training methodologies, product managers on customer requirements, and infrastructure teams on compute and storage dependencies.
- Raise the bar: Participate in Amazon's hiring process as a Bar Raiser or interviewer. Foster a culture of technical excellence, ownership, and continuous improvement.
- Influence the roadmap: Translate customer needs and business goals into a prioritized engineering roadmap. Make sound trade-offs between speed, quality, and scope.
About the team
We are building the next generation of model customization tooling that empowers customers to tailor foundation models to their domains — from healthcare and finance to retail and robotics. Our mission is to make model customization accessible, reliable, and cost-effective at any scale. You will join a team that values customer obsession, technical depth, and a bias for action. This is a Boston-based role with the opportunity to shape a new team and product area from the ground up.
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 engineering experience
- 3+ years of providing technical leadership and project management for all aspects of the software development lifecycle experience
- 3+ years of developing large-scale, multi-tiered distributed software systems using service-oriented architecture experience
- Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations
- 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 communicating with users, other technical teams, and senior leadership to collect requirements, describe software product features, technical designs, and product strategy
- Experience with training and deploying machine learning systems to solve large-scale optimizations, or experience in development or technical support
- Experience with AWS services (EC2, S3, SageMaker, EKS, Step Functions) or equivalent cloud platforms
- Strong written and verbal communication skills; ability to write crisp narratives and influence senior leadership
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, MA, Boston - 184,900.00 - 250,200.00 USD annually
How we rate this
Software Development Manager, AWS SageMaker at Amazon rates 90 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. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- How do you decide that one model's output is better than another's for a given task?
- Tell me about a project where team management was part of your work. What did you do?
- Tell me about a project where machine learning infrastructure was part of your work. What did you do?
- Tell me about a project where model fine tuning was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Fine Tuning, AI Evaluation, Team Management, Machine Learning Infrastructure, and Model Fine Tuning. 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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