Senior Delivery Consultant - Data , Professional Services, AWSI HCLS

Amazon is hiring a Senior Delivery Consultant - Data , Professional Services, AWSI HCLS 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

Works on AI ●●●○ is how Level rates this AI consultant role: 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 Bedrock, SageMaker and Databricks among its tools and skills.
Amazon has 20,000+ other open roles on Level.

AI in this role

Design modern data platforms and RAG architectures to prepare enterprise healthcare and life sciences systems for AI workloads.

BedrockSageMakerDatabricksAWSVector Stores

prompt-engineeringragai-agentsdata-engineeringknowledge-graphshipaagxpmachine-learning

The Amazon Web Services Professional Services (ProServe) team is seeking a Delivery Consultant specializing in Data to join our Healthcare and Life Sciences (HCLS) practice. You will be at the center of the most consequential shift in enterprise technology: making organizations truly AI-ready. Every agentic AI system, every foundation model grounded in enterprise knowledge, and every GenAI application that moves from prototype to production depends on the data layer beneath it - and that's what you build.

You will design and implement modern data platforms (lake, lakehouse, mesh), architect data pipelines that transform raw, fragmented data estates into governed, AI-ready assets; and design and implement enterprise RAG architectures, vector stores, semantic ontologies, and knowledge graph architectures that allow foundation models and AI agents to reason accurately, access data securely, and execute autonomously within regulated environments. You will work hands-on inside HCLS customer environments with complex data lineage, regulatory overlays (GxP, HIPAA, CDISC), and legacy systems, and ship production-grade data products that serve multiple downstream consumers, from ML model training to agentic orchestration layers.

The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using AWS services. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing and AI transformation initiatives.

This role requires approximately 50% co-location on site with customer, AWS and partner teams within the U.S.

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Key job responsibilities
- Design and implement production-grade data pipelines, data lakes, lakehouses, and data mesh architectures within enterprise HCLS environments, integrating with legacy systems and existing data governance frameworks

- Build data products that serve multiple downstream applications and use cases — from AI/ML model training to agentic AI systems, ensuring data quality, lineage, and reliability at scale

- Operate with a high degree of autonomy within fast-moving delivery engagements, making judgment calls on data modeling, pipeline design, and architecture without waiting for perfect specifications or constant oversight

- Navigate complex data access, security, and privacy requirements unique to pharma and healthcare including GxP compliance constraints, HIPAA, and regulatory data governance frameworks

- Architect contextual knowledge layers, including ontologies and knowledge graphs leveraging AWS Context, Amazon Bedrock Knowledge Bases, and custom ontology extensions to equip AI agents with the vocabulary and guardrails to reason accurately and execute autonomously within regulated environments

- Collaborate across organizational boundaries to secure data access, understand source system context, and resolve data quality challenges with teams across customer IT, business, and partner organizations

- Deliver iteratively when requirements are ambiguous, translating incomplete business needs into well-architected data solutions that can evolve as customer understanding matures

- Apply AI-DLC (AI-accelerated Development Life Cycle) methodologies to data delivery to redesign data workflows to become AI-native for accelerated scale and pace

About the team
ABOUT AWS:

Diverse Experiences
Amazon 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.

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.

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 and 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.

Basic qualifications

- 5+ years of cloud architecture and solution implementation experience
- Bachelor's degree, or 7+ years of professional or military experience
- 5+ years of experience in data engineering, data architecture, and/or data platform development, with hands-on implementation of production data pipelines
- Experience with modern data platform design patterns, including data lakes, lakehouses, data mesh, and zero-ETL patterns and streaming architectures, using services such as Amazon SageMaker Lakehouse, SageMaker Unified Studio, Amazon S3 Tables, Amazon Redshift, and zero-ETL integrations
- Experience with architecting and engineering ontologies and knowledge graphs in enterprise environments

Preferred qualifications

- AWS certifications in Data Analytics or Machine Learning Specialty preferred
- Experience in the healthcare and life sciences industry, including familiarity with compliance and security frameworks (HIPAA, GxP) and clinical data standards (OMOP, CDISC, FHIR)
- Hands-on experience with Apache Iceberg, Spark, Databricks, Snowflake, Kafka, or equivalent distributed data processing frameworks
- Experience designing and implementing knowledge graph architectures, ontology models, or semantic data layers that support AI/ML and agentic AI systems
- Experience with data governance and cataloging tools (e.g., AWS Glue Data Catalog, Collibra, Alation) and data lineage tracking and designing data access patterns that support identity and least-priviledge access
- Experience collaborating with customer business teams, IT, and partner organizations to understand data requirements and resolve access challenges and conveying technical concepts to both technical and business audiences.
- Proficiency in AI-DLC or equivalent AI-accelerated development methodologies — including prompt engineering as a development discipline, mob programming with AI, and experience validating AI-generated data pipeline code for production deployment in regulated environments

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, IL, Chicago - 153,600.00 - 207,800.00 USD annually
USA, MA, Boston - 153,600.00 - 207,800.00 USD annually
USA, NC, Raleigh - 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, VA, Arlington - 153,600.00 - 207,800.00 USD annually
USA, WA, Seattle - 153,600.00 - 207,800.00 USD annually

How we rate this

Senior Delivery Consultant - Data , Professional Services, AWSI HCLS at Amazon rates 65 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.

Classification

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.

Key facts

Senior Delivery Consultant - Data , Professional Services, AWSI HCLS is an open job at Amazon.
Level rates this role AI Level 3 of 4: Works on AI.
The listed salary is $177k-$239k a year.
The role is based in US, MA, Boston and is marked remote.
The job was posted on July 1, 2026.
Seniority: senior.
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

Prompt engineeringRAGAI agentsData EngineeringKnowledge GraphsHipaaGxpMachine learning

Also common in AI consultant jobs at this level

Python LLM SQL Java Azure Google Cloud

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 structure and test a prompt to get consistent output from a language model?
How would you design a retrieval step so the model answers from real data instead of guessing?
How do you decide when an AI agent can act on its own versus asking for approval first?
Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where knowledge graphs was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Prompt engineering, RAG, AI agents, Data Engineering, and Knowledge Graphs. 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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