Cleco · 7 hours ago
AI Solution Architect
Pineville, LA
Full-time
Onsite
Senior Level
5+ years expCleco is committed to powering a cleaner, smarter future for Louisiana through innovative energy solutions. The AI Solution Architect II is responsible for architecting, engineering, and operationalizing enterprise AI solutions, ensuring they are scalable, secure, and performant while collaborating with various technology and cybersecurity teams.
Electrical DistributionEnergyRetail
Responsibilities
Champions a corporate culture that emphasizes transparency, integrity, safety, environmental responsibility, employee development, diversity and inclusion, customer service, and operational excellence
Architect and engineer end-to-end AI solutions, platforms, and pipelines to address specific business needs, ensuring scalability, security, and operational readiness; provide implementation guidance upon delivery
Define and govern AI architecture standards, platforms, and reference frameworks, guiding decisions on governance, methodologies, and operational processes to ensure safety and compliance at scale
Design and implement AI solutions across cloud and hybrid environments, optimizing for performance, cost-efficiency, and resource utilization
Evaluate AI/ML models and system architectures, including scalability, computational efficiency, accuracy, robustness, and detection of model drift or anomalies
Ensure seamless integration of AI solutions into Cleco’s enterprise IT ecosystem, including SaaS, PaaS, and IaaS environments, in alignment with enterprise architecture and integration standards
Partner with cybersecurity, privacy, and risk teams to identify vulnerabilities, implement security controls, and conduct risk assessments for AI systems and data pipelines
Streamline cross-functional collaboration by coordinating architects, engineers, and business stakeholders to identify and prioritize AI requirements
Navigate technical complexity by developing scenarios and recommendations for selecting AI platforms, frameworks, and tools that complement one another and meet business objectives
Enable AI testing, validation, and release readiness, including designing test strategies, validating system behavior, supporting defects analysis, and enabling CI/CD and ModelOps pipelines for AI deployments
Own and maintain AI architecture documentation, standards, integration patterns, and lifecycle artifacts, ensuring reusability, compliance, and auditability across AI solutions
Qualification
Required
A bachelor's degree in computer engineering, computer science, software engineering, artificial intelligence, mathematics, or a related quantitative or natural science discipline is required; a master's degree or Ph.D. is highly preferred or a minimum of five years of experience building and operating production-grade AI/ML systems, including principal-level ownership of MLOps pipelines, model deployment, monitoring, and cloud-native platform architecture in distributed enterprise environments
A minimum of three years experience building and operating production-grade AI/ML systems, including principal-level ownership of MLOps pipelines, model deployment, monitoring, and cloud-native platform architecture in distributed enterprise environments
Proven experience working with large language models and foundation models, including designing architectures optimized for cost efficiency, scalability, and operational performance
Experience architecting AI solutions incorporating advanced techniques such as natural language processing (NLP), vector databases, knowledge graphs, and retrieval-augmented generation (RAG) architectures
Skilled in selecting and architecting AI frameworks (e.g., TensorFlow, PyTorch, Hugging Face), cloud platforms (Azure, AWS), and orchestration technologies (Docker, Kubernetes) for scalable enterprise AI deployments
Ability to apply AI system testing and validation techniques (e.g., pairwise testing, A/B testing, back-to-back testing) across operating systems and deployment environments
Advanced understanding of enterprise integration architectures, APIs, data pipelines, and event-driven systems
Excellent written and verbal communication skills, with the ability to explain complex AI architectures and trade-offs to technical and non-technical stakeholders
Strong documentation skills with the ability to produce diagrams, demos and technical artifacts that make AI architectures comprehensible and actionable
Strong working knowledge of ModelOps, AI engineering, DevOps, and MLOps practices, including CI/CD pipelines, monitoring, and production support models
Progression to this level is strictly restricted based on critical individual capabilities and business requirements; must be supported by market survey data
Company
Cleco
At Cleco, we consider it an honor to provide the next generation with the resources they need for personal and professional success through sustainable, clean and safe energy solutions.
1001-5000 employees
H1B Sponsorship
Cleco has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (8)
2024 (7)
2023 (3)
2022 (2)
2021 (3)
2020 (5)
Funding
Current Stage
Public CompanyTotal Funding
$175M2024-11-25Post Ipo Debt· $175M
2014-10-20Acquired
1981-11-06IPO
Leadership Team
Jeremy Kliebert
Vice President, Corporate Development, Deputy General Counsel and Chief Compliance Officer
Brittany Trahan
HR Business Partner
Recent News
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