Sr. Delivery Consultant - AI/ML, AWSI Energy SDT

Amazon
Houston, TX, USA2026-09-01ONSITE

About the job

Join AWS Professional Services' Energy segment in Houston as a Data Scientist and help global enterprises turn complex data into real business impact with AI. You’ll design, build, validate, and deploy end-to-end machine learning and deep learning solutions on AWS—working alongside Big Data and DevOps specialists to take models from discovery through production.

Responsibilities

• Partner with enterprise and public-sector customers to identify high-value AI/ML opportunities and translate business challenges into scalable cloud solutions

• Work with customer business leaders, data teams, IT teams, and product owners to assess data, build and validate ML/DL models, and communicate results

• Collaborate with AWS consultants from other specialty disciplines to deploy, monitor, and retrain models

• Solve problems including forecasting, fraud or anomaly detection, personalization, document automation, and operational optimization

Qualifications

Minimum

• 7+ years of technical specialist, design and architecture experience

• 3+ years of cloud based solution (AWS or equivalent), system, network and operating system 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

• Bachelor's degree, or 7+ years of professional or military experience

Preferred

• 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

• Experience in designing and operationalizing agentic AI systems using patterns such as multi-agent orchestration, tool-use agents, and workflow orchestration — ideally leveraging AWS services (Amazon Bedrock, AgentCore)