招聘
Interested in building the future of intelligent AI agents? The Agentic AI organization at AWS is on a mission to empower developers and enterprises to store and retrieve memory for autonomous agents that can reason, plan, and act using state-of-the-art GenAI systems. Our Agent Core Memory team plays a central role in this mission by enabling both short and long term memory capabilities of agentic systems.
In this role, you will build a new AWS service that is going to be trend setting in the Gen AI field. This is an area that requires solving hard engineering challenges to enable machine learning powered solutions for our customers. As a tier zero Amazon service our solutions have to be scalable, efficient, and fault tolerant. Experience with machine learning systems is preferred, but not required. You will deliver some of our most strategic technical projects, deliver large scalable systems, design new software systems and have a significant bottom-line impact on our business and competitive position. In addition to delivering critical software, you will draw from a deep and broad technical expertise to mentor engineers and provide leadership on complex technical issues. This position within the Agentic AI team presents a unique and rare opportunity to get in on the ground floor within a fast growing business and help shape the technology, product and the business. A successful candidate will bring deep technical and software expertise, desire to have an industry wide impact and ability to work within a fast moving, startup environment in a large company to rapidly deliver services that have a broad business impact.
As a SDE, you will be responsible for designing, developing, testing, and deploying distributed machine learning systems and large-scale solutions for our world-wide customer base. In this, you will collaborate closely with a team of applied scientists to influence our overall strategy. You will also drive the system architecture, spearhead best practices that enable a quality product, and help coach and develop junior engineers. A successful candidate will have an established background in engineering large scale software systems, a strong technical ability, great communication skills, and a motivation to achieve results in a fast paced environment.
Agentic AI drives innovation at the forefront of artificial intelligence, enabling customers to transform their businesses through cutting-edge AI solutions. We build and deliver the foundational AI services that power the future of cloud computing, helping organizations harness the potential of AI to solve their most complex challenges. Join our dynamic team of AI/ML practitioners, applied scientists, software engineers, and solution architects who work backwards from customer needs to create groundbreaking technologies. If you're passionate about shaping the future of AI while making a meaningful impact for customers worldwide, we want to hear from you.
About the team
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge-sharing and mentorship. Our team members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future.
Basic Qualifications
- 3+ years of non-internship professional software development experience
- 3+ years of programming with at least one software programming language experience
- 3+ years of contributing to new and current systems architecture and design (architecture, design patterns, reliability and scaling) experience
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
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, NJ, Jersey City - 158,100.00 - 213,800.00 USD annually
USA, NY, New York - 158,100.00 - 213,800.00 USD annually
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关于Amazon

Amazon
PublicAmazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.
10,001+
员工数
Seattle
总部位置
$1.5T
企业估值
评价
2.9
10条评价
工作生活平衡
2.8
薪酬
3.7
企业文化
2.5
职业发展
2.3
管理层
2.1
35%
推荐给朋友
优点
Good pay and compensation
Strong benefits package
Flexible scheduling options
缺点
Poor management and leadership
Limited growth and promotion opportunities
High stress and demanding work environment
薪资范围
4个数据点
L2
L3
L4
L5
L6
L2 · Data Analyst L2
0份报告
$108,330
年薪总额
基本工资
$43,332
股票
$54,165
奖金
$10,833
$75,831
$140,829
面试经验
10次面试
难度
3.7
/ 5
时长
21-35周
录用率
20%
体验
正面 10%
中性 10%
负面 80%
面试流程
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Onsite/Virtual Loop
6
Team Matching
7
Offer
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Leadership Principles
Technical Knowledge
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