Professional Services II - Amz23491.4

Amazon Amazon · Big Tech · NY +1 · Corporate Operations

This role involves designing and building end-to-end Generative AI and Machine Learning solutions using AWS managed services, focusing on customer engagements and modernization of data platforms. The role requires expertise in areas like RAG, multi-agent workflows, and integrating enterprise data sources into cloud environments.

What you'd actually do

  1. 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.
  2. Participate in pre-sales and work to understand customer requirements, create proposals and packaged Modern Data Architecture, Machine Learning and Generative AI Architecture offerings.
  3. 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.
  4. 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.
  5. Lead a team through customer engagements and responsible for achieving business outcomes for the customers.

Skills

Required

  • Python
  • SQL
  • Java
  • Terraform
  • prompt engineering
  • retrieval-augmented generation architectures
  • multi-agent workflows
  • AWS cloud services
  • SDKs
  • CI/CD pipelines
  • data analytics
  • visualization solutions
  • KPI development
  • executive dashboards
  • financial analytics

Nice to have

  • Machine Learning
  • Generative AI
  • Agentic AI
  • technical analysis
  • generative AI outputs
  • large language model–based solutions
  • knowledge base integration

What the JD emphasized

  • 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

Other signals

  • building production-grade Generative AI solutions
  • designing end-to-end architectures
  • customer engagements
  • AWS managed services