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Senior Deep Learning Architect, Agentic AI Professional Services

Amazon

Senior Deep Learning Architect, Agentic AI Professional Services

Amazon

Dallas, TX, USA

·

On-site

·

Full-time

·

1mo ago

Compensation

$153,600 - $228,600

Benefits & Perks

Healthcare

401(k)

Equity

Parental Leave

Mental Health

Flexible Hours

Healthcare

401k

Equity

Parental Leave

Mental Health

Flexible Hours

Required Skills

Python

TypeScript

SQL

Deep learning

AI/ML

Agentic AI

Cloud architecture

Serverless architecture

Object-oriented programming

The Amazon Web Services Agentic AI Professional Services Experience team is seeking a skilled deep learning architect. In this role, you'll design and build Pro Serve AI agents that automate and accelerate consulting services delivery for all customer workloads, work closely with Pro Serve agents on customer engagements to accelerate solutions that meet customer's technical requirements and business objectives. You'll be a key player in driving customer success through Pro Serve agents, providing technical expertise and best practices. You will lead or contribute to internal agent build work streams and customer-focused project teams as a technical leader, and work with Pro Serve agents to perform hands-on development of technical solutions with exceptional quality. Possessing a deep understanding of AWS products and services, you will be proficient in architecting complex, scalable, and secure AI/ML and GenAI solutions. You'll work closely with stakeholders to gather requirements, assess current infrastructure, and propose effective strategies and solutions. As trusted advisors to our customers and partners, providing guidance on industry trends, emerging technologies, and innovative solutions, you will be responsible for building new agents and rolling them out to builders internally and customers and partners. leading or advising the delivery teams or customer builders, ensuring adherence to best practices, optimizing performance and minimizing risks.

  • Key job responsibilities
  • Hands-on design and build AI agents that support high-performance, reliable, scalable, and secure workloads.
  • Collaborating with cross-functional teams to test and evaluate agent capabilities and roll out to internal and external users
  • Serving as a catalyst to enable Pro Serve builders and trusted advisor to customers on how to use Pro Serve agents to accelerate solution delivery
  • Sharing knowledge and best practices through mentoring, training, publication, presentation, and creating reusable artifacts.
  • Ensuring solutions meet industry standards and supporting customers in advancing their AI/ML, GenAI, and cloud adoption strategies.

About the team
Agentic AI Pro Serve Experience (APEX) is an AI-first organization within AWS Professional Services (Pro Serve), providing Pro Serve agents for customer engagements and accelerating go-live to under 45 days.

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

  • 7+ years of consulting, design and implementation of serverless distributed solutions experience
  • 5+ years of software development with object oriented language experience
  • 7+ years of external or internal customer facing, complex and large scale project management experience
  • 5+ years of cloud architecture and solution implementation experience
  • 5+ years developing with Python, Typescript, SQL, and at least one additional programming language (e.g., Java, Scala, JavaScript). Proficient with leading ML libraries and frameworks (e.g., Tensor Flow, Py Torch).
  • 3+ years developing AI/ML including agentic AI applications, with a proven track record of building and deploying on cloud.

Preferred Qualifications

  • degree in advanced technology, or AWS Professional level certification
  • Knowledge of AWS services including compute, storage, networking, security, databases, machine learning, and serverless technologies
  • Knowledge of security and compliance standards including HIPAA and GDPR
  • Experience in performance optimization and cost management for cloud environments
  • Experience communicating technical concepts to diverse audiences in pre-sales environments

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, NY, New York - 169,000.00 - 228,600.00 USD annually
USA, TX, Austin - 153,600.00 - 207,800.00 USD annually
USA, TX, Dallas - 153,600.00 - 207,800.00 USD annually
USA, WA, Seattle - 153,600.00 - 207,800.00 USD annually

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About Amazon

Amazon

Amazon

Public

Amazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.

10,001+

Employees

Seattle

Headquarters

Reviews

2.9

10 reviews

Work Life Balance

2.8

Compensation

3.7

Culture

2.5

Career

2.3

Management

2.1

35%

Recommend to a Friend

Pros

Good pay and compensation

Strong benefits package

Flexible scheduling options

Cons

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

Salary Ranges

2 data points

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Junior/L3 · Data Scientist L4

0 reports

$181,968

total / year

Base

-

Stock

-

Bonus

-

$154,672

$209,264

Interview Experience

10 interviews

Difficulty

3.7

/ 5

Duration

21-35 weeks

Offer Rate

20%

Experience

Positive 10%

Neutral 10%

Negative 80%

Interview Process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge