> Markdown version of [/jobs/ext/3691770-sr-delivery-consultant-ai-ml-awsi-energy-sdt](https://www.wearedevelopers.com/jobs/ext/3691770-sr-delivery-consultant-ai-ml-awsi-energy-sdt). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Delivery Consultant - AI/ML, AWSI Energy SDT - **Company:** Amazon.com, Inc. - **Location:** Houston, TX, United States - **Experience:** Expert - **Salary:** $153,600.0 - $207,800.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Big Data, Cloud Computing, Cloud Engineering, Databases, DevOps, Machine Learning, Performance Tuning, Cloud Services, Multi-Agent Systems, AgentCore, AI Platforms, Amazon Bedrock, Serverless Computing - **Published:** October 11, 2026 - **Apply:** https://www.careerjet.com/job/usf46419927f9b1bd423550ca25499185a/eaa ## About the Role 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 Qualifications - 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) ## Description 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. This is an opportunity to solve high-value customer problems using AWS AI services, modern ML/DL frameworks, and large-scale cloud infrastructure, while exploring emerging approaches in areas such as model monitoring and retraining. If you are curious, customer-focused, love diving deep into data, and want to grow with a collaborative team at the forefront of cloud AI, this role offers meaningful technical challenges, mentorship, and strong career development opportunities in a high-growth industry segment for AWS cloud., As an experienced Professional Services Sales Leader, you will be responsible for: * Leading and developing a high-performing team of Account Executives and Cloud Architects * Developing and supporting execution of sales strategies to meet team targets and drive revenue growth * Managing customer relationships, ensuring high satisfaction and identifying new opportunities * Leveraging deep AWS knowledge to guide sellers in proposing optimal solutions * Monitoring and analyzing key performance indicators, ensuring accurate reporting and forecasting to optimize operational processes and manage risk A day in the life As an AWS Professional Services Data Scientist, you will partner with enterprise and public-sector customers to identify high-value AI/ML opportunities and translate business challenges into scalable cloud solutions. Day to day, you will work with customer business leaders, data teams, IT teams, and product owners to assess data, build and validate ML/DL models, and communicate results. You will collaborate with AWS consultants from other specialty disciplines to deploy, monitor, and retrain models. Typical problems include forecasting, fraud or anomaly detection, personalization, document automation, and operational optimization.