Software Development Manager, Project Dawn

Amazon is hiring a Software Development Manager, Project Dawn 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.
Tools and skills the posting cites include Bedrock, SageMaker and Python.
Level classifies it as a lead role.
Level lists 21,000+ other open roles at Amazon.
The role was posted within the past week.

AI in this role

Lead a software engineering team building web-scale data extraction infrastructure powered by large language models for e-commerce catalogs.

bedrocksagemakerpythonaws

machine-learninglarge-language-modelsteam-leadershipinfrastructuredata-extraction

As an SDM in the OAS Offers Tech org, you will own the engineering infrastructure that determines the breadth of off-Amazon merchant selection available to Amazon customers — spanning web-scale data ingestion, structured extraction, and catalog contribution.
This role sits at a genuinely hard frontier: applying large language models and hybrid extraction strategies to the inconsistent structure of millions of e-commerce websites, while maintaining the reliability and throughput requirements of a production catalog system. The right extraction approach varies by merchant, by platform, and by the maturity of the science models your team hosts and serves — and navigating those tradeoffs in real time, at scale, is one side of the challenge. The other is guiding the team through the internal complexity of Amazon's catalog — the data contracts, ingestion standards, quality thresholds, and partner system requirements that govern whether extracted merchant data successfully becomes discoverable, purchasable selection for customers. This role sits at the boundary between web-scale extraction and Amazon's catalog infrastructure, and engineering judgment on both sides is required.
You will collaborate with Science and Product partners in the Selection & Coverage pod, own the infrastructure that hosts and deploys extraction models in production, and be the engineering owner of OAS's selection coverage strategy.

Key job responsibilities
* Lead, hire, and develop a team of software development engineers across multiple workstreams, maintaining a high engineering bar and a culture of ownership
* Collaborate with Science and Product partners in the OAS Offers org, align on workstream prioritization and surface engineering tradeoffs that need leadership input
* Translate Science team model improvements into production-ready systems and establish repeatable deployment pipelines that reduce time-to-production for new model checkpoints
* Set and own the engineering delivery roadmap against committed KPI ramp targets; identify risks early and provide clear path-to-green or escalation when milestones are at risk
* Make and document active engineering tradeoffs — when to run strategies in parallel vs. sequence them, how to balance near-term funnel loss recovery against strategic infrastructure investments
* Define and maintain operational excellence standards for extraction infrastructure: availability, latency, data quality, and cost efficiency

Basic qualifications

- 3+ years of engineering team management experience
- 7+ years of engineering experience
- 7+ years of leading the definition and development of multi tier web services experience
- 3+ years of providing technical leadership and project management for all aspects of the software development lifecycle experience
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
- 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
- Experience in communicating with users, other technical teams, and senior leadership to collect requirements, describe software product features, technical designs, and product strategy
- Experience in recruiting, hiring, mentoring/coaching and managing teams of Software Engineers to improve their skills, and make them more effective, product software engineers

Preferred qualifications

- Experience productionizing machine learning models — specifically building the infrastructure that hosts, serves, and deploys models in production, in partnership with Applied Science teams
- Familiarity with web-scale crawling, data extraction, or content ingestion systems
- Experience with LLM-based applications in production, including prompt management, output validation, and latency/cost tradeoffs
- Prior experience managing teams that work at the intersection of rule-based and model-based systems
- Experience building systems on AWS (ECS, SageMaker, Bedrock, Glue) at production scale
- Demonstrated experience running a metric-driven team — committing to KPI ramps, reporting against them honestly, and identifying the engineering levers that move the number

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

Software Development Manager, Project Dawn at Amazon rates 85 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.

Classification

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.

Key facts

Software Development Manager, Project Dawn is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $185k-$250k a year.
The role is based in US, WA, Seattle.
The job was posted on October 22, 2026.
Seniority: lead.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Machine learningLarge Language ModelsTeam LeadershipInfrastructureData ExtractionBedrockSageMakerPython

Questions you could be asked

Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where large language models was part of your work. What did you do?
Tell me about a project where team leadership was part of your work. What did you do?
Tell me about a project where infrastructure was part of your work. What did you do?
Tell me about a project where data extraction was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Machine learning, Large Language Models, Team Leadership, Infrastructure, and Data Extraction. 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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