Location This is onsite role based in Houston, TX About the job you9re considering Capgemini is seeking an enthusiastic and driven AI/ML Engineer / GenAI Engineer / Data Scientist to join our dynamic Energy & Utilities sector team. This role is designed for emerging talent passionate about leveraging Artificial Intelligence to solve complex industry challenges. The ideal candidate will contribute to innovative projects, applying advanced AI/ML techniques to optimize operations, enhance decision-making, and drive digital transformation for our clients. This is a client-facing role requiring strong technical expertise, communication skills, and a passion for AI-driven innovation. Your Role  Collaborate with senior consultants and client teams to identify business challenges and opportunities for AI-driven solutions within the Energy & Utilities sector.  Assist in the design, development, and deployment of AI/ML models, including Generative AI and Predictive AI solutions.  Support data collection, cleansing, validation, and preprocessing activities for AI initiatives.  Work with leading cloud platforms including Azure, AWS, and GCP, leveraging their AI and machine learning services.  Utilize Databricks, PySpark, and modern AI frameworks to develop scalable analytics and AI solutions.  Develop agentic AI workflows and intelligent agents to automate business processes and improve operational efficiency.  Design and implement Retrieval-Augmented Generation (RAG) solutions using modern AI technologies and frameworks. Your skills and experience  Bachelor9s or Master9s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related quantitative field.  Minimum of 2 years of professional work experience in Data Science, Artificial Intelligence, or Machine Learning roles.  Demonstrated experience within the Energy & Utilities sector.  Strong foundational knowledge of Artificial Intelligence, Machine Learning, and Deep Learning concepts.  Proficiency in Python or other AI-centric programming languages.  Experience working with Generative AI concepts including GPT, Claude, Large Language Models (LLMs), and foundation models.  Knowledge of MLOps practices including model deployment, monitoring, governance, and lifecycle management.  Experience with LangChain, Retrieval-Augmented Generation (RAG), prompt engineering, and AI orchestration frameworks.  Hands-on experience developing and consuming REST APIs, JSON-based services, authentication mechanisms, and integration patterns.  Experience with deployment tools such as Azure DevOps, Docker, AWS ECS, EKS, Fargate, CloudFormation, CodeDeploy, and CI/CD pipelines.  Strong understanding of data engineering principles and experience working with SQL and NoSQL databases such as MySQL, MongoDB, and Redis.  Experience utilizing Databricks, PySpark, and cloud-based analytics platforms.  Strong analytical thinking, problem-solving, and critical reasoning skills.  Excellent communication, presentation, and interpersonal skills with the ability to effectively engage in client-facing situations.  Ability to quickly learn emerging technologies and adapt within fast-paced, evolving environments.  Experience working in Agile/Scrum delivery environments.  Strong collaboration skills with cross-functional and geographically distributed teams. Preferred Experience  Prior experience with OFSE (Oil Field Services & Equipment) or broader Oil & Gas industry operations.  Experience with data visualization tools and techniques.  Hands-on experience with Machine Learning frameworks such as TensorFlow, PyTorch, and scikit-learn.  Experience in Natural Language Processing (NLP) solutions and applications. #LI-SD1 The base compensation range for this role in the posted location is $53,580 to $122,400 Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law. The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction. These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity. It is not typical for candidates to be hired at or near the top of the posted compensation range. In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws. Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:  Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave  Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)  Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)  Life and disability insurance  Employee assistance programs  Other benefits as provided by local policy and eligibility Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini9s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.