Job Summary
We are seeking a highly experienced and technically driven professional to design and deliver scalable, secure AI solutions that align with enterprise strategy and standards. This role blends hands-on technical leadership with architectural guidance, requiring close collaboration with data, platform, security, and application teams to seamlessly integrate AI capabilities into core business systems. The ideal candidate will contribute meaningfully to solution design, support implementation teams through execution, and play an active role in maturing enterprise AI platforms, patterns, and governance frameworks.
Job Summary
We are seeking a highly experienced and technically driven professional to design and deliver scalable, secure AI solutions that align with enterprise strategy and standards. This role blends hands-on technical leadership with architectural guidance, requiring close collaboration with data, platform, security, and application teams to seamlessly integrate AI capabilities into core business systems. The ideal candidate will contribute meaningfully to solution design, support implementation teams through execution, and play an active role in maturing enterprise AI platforms, patterns, and governance frameworks.
Open to Minneapolis or Denver
Responsibilities
- Design and implement production AI and GenAI solutions, including LLM-based systems, that meet enterprise scalability and security requirements
- Lead architecture design for reliable, scalable AI platforms and services aligned to enterprise strategy and standards
- Apply AI architecture patterns, guardrails, and principles consistently across solutions to ensure quality and compliance
- Collaborate closely with engineering teams to design, build, and optimize AI solutions from conceptual design through to working implementation
- Integrate AI capabilities into existing enterprise systems, workflows, and analytics platforms
- Design AI solutions that leverage enterprise data assets, ensuring data pipeline integrity and data quality considerations are addressed
- Identify and mitigate AI risks including model performance degradation, bias, explainability gaps, and operational robustness concerns
- Translate complex AI concepts into clear, actionable architectural guidance for delivery teams and business stakeholders
- Partner effectively across data, platform, security, and application teams to drive cohesive AI solution delivery
- Contribute to roadmap discussions and technical decision‑making in support of enterprise AI maturity and business outcomes
- Support the development and adoption of enterprise AI governance frameworks, patterns, and best practices
Skills
- Hands-on experience designing and implementing production AI and GenAI solutions, including LLM-based architectures
- Proficiency in AI model development, prototyping, and deployment across the full ML lifecycle including training, inference, evaluation, and iteration
- Strong expertise in AI architecture design for scalable, reliable platforms and services
- Experience integrating AI capabilities into enterprise systems using cloud-native architectures and modern development practices
- Solid understanding of data pipelines, data platforms, and data quality considerations that underpin AI workloads
- Ability to apply architectural standards and governance principles to ensure alignment with enterprise technology strategy
- Awareness of AI risk domains including model bias, explainability, and operational robustness
- Excellent communication skills with the ability to translate complex technical concepts for both technical and non-technical audiences
- Strong cross‑functional collaboration skills with the ability to partner across data, platform, security, and application teams
- Ability to move fluidly between high‑level architectural thinking and hands‑on delivery execution
Experience
- Demonstrated experience designing and delivering enterprise-scale AI and machine learning solutions in production environments
- Proven track record of hands‑on AI architecture work including LLM integration and GenAI solution delivery
- Experience working within large, complex organizations with established technology governance and enterprise architecture standards
- Background collaborating with cross‑functional engineering, data, and platform teams on AI solution design and implementation
- Experience contributing to AI platform maturity, including the development of reusable patterns, standards, and guardrails
Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical discipline
- Relevant cloud platform certifications (e.g., AWS, Azure, or Google Cloud) with a focus on AI and machine learning services are an asset
- Professional certifications in AI, machine learning, or enterprise architecture are considered an advantage
The closing date for applications for this job posting is 10/4/2026.
Should you require any accommodations in responding to this job posting or at any stage during the application process, kindly e-mail : xcelenergyprogramoffice@magnitglobal.com
Pay Rate Range
80.31 - 107.08 USD hourly