Sr. Delivery Consultant - AI/ML, AWS Professional Services
Amazon is hiring a Sr. Delivery Consultant - AI/ML, AWS Professional Services for a remote role open to applicants in United States. It pays $177k-$239k a year and Level rates it ; you can apply on Amazon.
Level's read on this job
- Level rates this AI consultant role Works on AI ●●●○: the daily work is on AI products, without building the model.
- Pay on this posting starts 17% higher than the typical AI consultant posting on Level.
- This is listed as a remote role.
- The posting mentions LangChain, LlamaIndex and LangGraph among its tools and skills.
- Amazon has 20,000+ other open roles on Level.
AI in this role
Design and implement GenAI and machine learning applications on AWS as a Senior Delivery Consultant.
The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Delivery Consultant to join our team at Amazon Web Services (AWS). In this role, you'll work closely with customers to design, implement, and manage AWS solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their cloud journey, providing technical expertise and best practices throughout the project lifecycle.
Possessing a deep understanding of AWS products and services, as a Delivery Consultant you will be proficient in architecting complex, scalable, and secure solutions tailored to meet the specific needs of each customer. You’ll work closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS. As trusted advisors to our customers, providing guidance on industry trends, emerging technologies, and innovative solutions, you will be responsible for leading the implementation process, ensuring adherence to best practices, optimizing performance, and managing risks throughout the project.
The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries.
Key job responsibilities
As an experienced Senior AI/ML Consultant, you will be responsible for:
Designing, implementing, and building complex, scalable, and secure GenAI and ML applications and models built on AWS tailored to customer needs
Providing technical guidance and implementation support throughout project delivery, with a focus on using AWS AI/ML services
Collaborating with customer stakeholders to gather requirements and propose effective model training, building, and deployment strategies
Acting as a trusted advisor to customers on industry trends and emerging technologies
Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts
About the team
About AWS:
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, 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 - Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness.
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 in the cloud.
Basic qualifications
- 5+ years of building machine learning models for business application experience
- 3+ years of hands-on experience with training, fine-tuning, evaluating, and deploying AI/ML models in production
- 3+ years of customer-facing work, engaging with customer executives, technologists or partners to solve business problems with advanced technologies experience
- Experience with cloud services related to machine learning (e.g., Amazon SageMaker) and generative AI applications
- 3+ years of coding, data querying languages (e.g. SQL), and scripting languages (e.g. Python)
Preferred qualifications
- Knowledge of AWS services including compute, storage, networking, security, databases, machine learning, and serverless technologies
- Knowledge of AWS services including SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch and AWS certifications
- 2+ years of experience with design, deployment, and evaluation of AI agents and orchestration approaches; experience with open source frameworks like LangChain, LangGraph, LlamaIndex, and/ or similar tools
- 5+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience using PyTorch or TensorFlow
- Experience building ML pipelines with MLOps best practices, including: data preprocessing, distributed & GPU training, model deployment, monitoring, and retraining; experience with container and CI/CD pipelines
- Domain expertise in healthcare and life sciences
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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, CA, Mountain View - 176,600.00 - 239,000.00 USD annually
USA, CO, Denver - 153,600.00 - 207,800.00 USD annually
USA, GA, Atlanta - 153,600.00 - 207,800.00 USD annually
USA, IL, Chicago - 153,600.00 - 207,800.00 USD annually
USA, NJ, Jersey City - 169,000.00 - 228,600.00 USD annually
USA, NY, New York - 169,000.00 - 228,600.00 USD annually
USA, TX, Dallas - 153,600.00 - 207,800.00 USD annually
USA, VA, Arlington - 153,600.00 - 207,800.00 USD annually
USA, VA, Herndon - 153,600.00 - 207,800.00 USD annually
USA, WA, Seattle - 153,600.00 - 207,800.00 USD annually
How we rate this
Sr. Delivery Consultant - AI/ML, AWS Professional Services at Amazon rates 75 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● 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
Also common in AI consultant jobs at this level
Pay
- This job starts at
- $177k
- Typical AI consultant job
- $151k
This posting starts 17% above the typical AI consultant job. See AI consultant jobs
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- Tell me about a project where machine learning was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI agents, Fine-tuning, ML Ops, Computer vision, and Machine learning. 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.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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