Manager, AI Engineer
$153,710–$267,030 year
On-siteDallas, Texas, United States
Job Summary
Design and develop end-to-end AI/ML solutions leveraging cloud platforms like Azure, AWS, and Google Cloud. Define solution architectures integrating LLMs, generative AI, and traditional ML with enterprise systems. Manage AI projects from architecture design through testing, ensuring adherence to MLOps, security, and compliance standards. Lead workshops with executives and stakeholders to shape AI roadmaps, while mentoring junior engineers and consultants. Collaborate with strategic alliance partners to incorporate ecosystem innovations into client engagements. Stay current with emerging technologies and evaluate their applicability for client needs.
Required Qualifications
- Minimum five years of recent professional experience in AI/ML, data engineering, or cloud solution engineering
- Minimum two years in a consulting or client-facing leadership role
- Minimum of a Bachelor's degree from an accredited college or university in computer science, data science, engineering, or related field
- Track record of delivering AI/ML solutions at enterprise scale, including integrations with core business systems
- Demonstrated ability to lead technical teams
- Demonstrated ability to manage deliverables
- Demonstrated ability to build trusted client relationships
- Hands-on expertise with at least two major cloud AI platforms (Azure AI/ML, AWS Bedrock/SageMaker, or Google Cloud Vertex AI)
- Proficiency in Python (and/or other relevant languages)
- Strong experience in API development
- Strong experience in microservices
- Strong experience in containers
- Strong experience in CI/CD pipelines
- Familiarity with MLOps frameworks (model monitoring, retraining pipelines, drift detection)
- Familiarity with modern data engineering practices
- Experience in building conversational AI/chatbots, generative AI use cases, or AI-powered automation solutions
- Knowledge of AI security
- Knowledge of data privacy
- Knowledge of governance
- Knowledge of ethical AI frameworks
- Strong problem-solving skills
- Ability to translate complex technical concepts for executives
- Excellent verbal and written communication skills
- Experience creating client-facing deliverables
- Willingness and ability to travel
- Applicants must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future
Desired Qualifications
- Master's degree from an accredited college or university
- Professional certifications in cloud AI/ML platforms (for example: Azure AI Engineer Associate, AWS ML Specialty, Google Cloud ML Engineer)
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