Gen AI Engineer

$84,000 - $142,000/Yr

NTT DATA - Plano, TX

Full-time - Mid Level

Onsite - Plano, TX

Professional, Scientific, and Technical Services

About the position

As a GenAI Engineer with NTT DATA, you will be at the forefront of innovation, leveraging your skills to design and implement cutting-edge AI solutions. This role offers a unique opportunity to work on transformative projects that drive business intelligence and decision-making across diverse industries. You will exercise expertise in ideating and developing AI/ML applications on prediction, recommendation, text analytics, computer vision, bots, and content intelligence. Your responsibilities will include applying statistical skills and advanced statistical techniques, demonstrating deep knowledge of ML frameworks such as TensorFlow, PyTorch, Keras, Spacy, and scikit-learn, and leveraging advanced knowledge of Python open-source software stacks such as Django or Flask. In this position, you will develop and implement GenAI solutions, collaborating with cross-functional teams to support the successful execution of AI projects for a diverse range of clients. You will assist in the design and implementation of GenAI use cases, projects, and POCs across multiple industries, and work on RAG models and Agents Frameworks to enhance GenAI solutions by incorporating relevant information retrieval mechanisms. Additionally, you will create and maintain data infrastructure to ingest, normalize, and combine datasets for actionable insights, ensuring client satisfaction and project success through effective communication of complex technical concepts to non-technical audiences. Conducting training sessions to enhance overall data science skills within the organization will also be part of your role.

Responsibilities

• Exercise expertise in ideating and developing AI/ML applications on prediction, recommendation, text analytics, computer vision, bots, and content intelligence.
• Apply statistical skills and advanced statistical techniques and concepts.
• Demonstrate deep knowledge of ML frameworks such as TensorFlow, PyTorch, Keras, Spacy, and scikit-learn.
• Leverage advanced knowledge of Python open-source software stack such as Django or Flask, Django Rest or FastAPI, etc.
• Develop and implement GenAI solutions, collaborating with cross-functional teams, and supporting the successful execution of AI projects for a diverse range of clients.
• Assist in the design and implementation of GenAI use cases, projects, and POCs across multiple industries.
• Work on RAG models and Agents Frameworks to enhance GenAI solutions by incorporating relevant information retrieval mechanisms and frameworks.
• Create and maintain data infrastructure to ingest, normalize, and combine datasets for actionable insights.
• Work closely with customers to understand their requirements and deliver customized AI solutions.
• Communicate complex technical concepts clearly to non-technical audiences.
• Conduct training sessions to enhance overall data science skills within the organization.

Requirements

• 1+ years of experience architecting high-impact GenAI solutions for diverse clients.
• 8+ years of experience participating in projects that focused on predictive analytics, data design, generative AI, AI/ML, and ML Ops.
• 3+ years of experience using Python.
• Bachelor's Degree required.
• Ability to travel at least 25%.

Nice-to-haves

• Experience with Nvidia NeMo Inference Manager (NIM) for deploying and managing AI models at scale.
• Demonstrates sound judgment with minimal support from practice executives through structured problem identification, mitigation, and resolution.
• Exhibits strong teamwork, consistently performing as a dependable team member with an excellent work ethic.
• Maintains a flexible 'can-do' attitude and a commitment to success.
• Professional verbal and written communication.

Benefits

• Competitive salary range of $120,525 - $200,875 based on experience and location.
• Opportunities for professional development and training.
• Inclusive and diverse work environment.