Professional Services II - AMZ23491.4

About the role

Collaborate with AWS field sales, pre-sales, training and support teams in efforts to help partners and customers learn and use AWS services such as Amazon Elastic Compute Cloud (EC2), Amazon S3, NoSQL DynamoDB, Relational Database Service (RDS), Elastic Map Reduce (EMR), AWS Glue, Amazon Athena, Amazon Redshift, AWS Machine Learning and Generative AI services like Amazon Bedrock, Amazon Bedrock AgentCore, Amazon SageMaker, Amazon Textract, and Amazon OpenSearch.

Responsibilities

• Participate in pre-sales and work to understand customer requirements, create proposals and packaged Modern Data Architecture, Machine Learning and Generative AI Architecture offerings.
• Work on delivery engagements which will include on-site and remote technical engagements with partners and stakeholders from diverse industries such Oil&Energy, Telecommunications, and Retail.
• Engage in the migration of existing applications and modernization of legacy data platforms, as well as development of new cloud-native analytics and agentic applications using AWS cloud services.
• Lead a team through customer engagements and responsible for achieving business outcomes for the customers.
• Lead the development, delivery, new architectural patterns, design principles and maintaining technical content for Data & Analytics, Machine Learning and Generative AI applications.
• Work with AWS engineering and support teams to convey partner and customer needs and feedback as input to technology roadmaps.
• Share real world implementation challenges and recommend new capabilities that would simplify adoption and drive greater value from use of AWS cloud services.

Requirements

• Master's degree or foreign equivalent degree in Computer Science, Engineering, Information Systems, Mathematics, or a related field and one year of experience in the job offered or a related occupation.
• One year of experience in the following skill(s): programming in Python, SQL, Java, or Terraform for data analytics, Machine Learning, and Agentic AI; experience translating technical analysis, machine learning, or generative AI outputs into actionable insights; developing or integrating generative AI or large language model–based solutions including prompt engineering, retrieval-augmented generation architectures, multi-agent workflows, and knowledge base integration; working with AWS cloud services, SDKs, and CI/CD pipelines; designing data analytics and visualization solutions including KPI development, executive dashboards, and financial analytics.

Qualifications

• One year of experience in the following skill(s): programming in Python, SQL, Java, or Terraform for data analytics, Machine Learning, and Agentic AI; experience translating technical analysis, machine learning, or generative AI outputs into actionable insights; developing or integrating generative AI or large language model–based solutions including prompt engineering, retrieval-augmented generation architectures, multi-agent workflows, and knowledge base integration; working with AWS cloud services, SDKs, and CI/CD pipelines; designing data analytics and visualization solutions including KPI development, executive dashboards, and financial analytics.

Skills

• Programming in Python, SQL, Java, or Terraform for data analytics, Machine Learning, and Agentic AI.
• Experience translating technical analysis, machine learning, or generative AI outputs into actionable insights.
• Developing or integrating generative AI or large language model–based solutions including prompt engineering, retrieval-augmented generation architectures, multi-agent workflows, and knowledge base integration.
• Working with AWS cloud services, SDKs, and CI/CD pipelines.
• Designing data analytics and visualization solutions including KPI development, executive dashboards, and financial analytics.

Benefits

The base pay range for this position in New York City is USD $179989 - $195400 (yr).

Pay

The base pay range for this position in New York City is USD $179989 - $195400 (yr).

Schedule

40 hours / week, 8:00am-5:00pm