Practice Architect II AI/ML

TEKsystems•Baltimore, MD

3d•Remote

About The Position

The AI Enhanced Azure Platform Practice Architect II serves as a senior enterprise consultant, architect, and technical leader within the Azure DevOps and AI practices. This role extends the traditional Azure Platform Architect scope by integrating AI-powered capabilities, tooling, and intelligent automation across client engagements. The PA reviews proposals and prepares project plans, works alongside delivery managers from all practices (InfoSec, Network, Data Center Support, Managed Services, etc.) to identify requirements, and advises clients on both DevOps best practices and AI-enhanced solutions. The position is expected to spend approximately 80% of time on delivery support and 20% on sales engineering support. This hybrid role bridges business needs with technical AI capabilities, ensuring that cloud and AI initiatives are scalable, secure, and aligned with organizational goals.

Requirements

Bachelor’s or Master’s degree in Computer Science, Management Information Systems, Engineering, or a related field — or commensurate real-world experience
8–10 years’ experience managing DevOps implementations across on-premises and cloud-based infrastructure deployments
3+ years focused on Azure AI solutions design and implementation
Prior management and consulting experience required
Hands-on experience with the Azure GUI, Azure CLI, PowerShell, ARM Templates, Azure DevOps, Terraform, and Git
Experience with Azure AI and ML services: Azure OpenAI, Azure Machine Learning, Cognitive Services, Azure Synapse Analytics, Azure Data Factory, and Databricks
Proficiency in Python, R, or other AI/ML programming languages
Strong understanding of cloud-native design principles and microservices architecture
Previous experience or familiarity with: VMware, Windows Server, Linux, LAN/WAN concepts
Experience with data engineering tools and frameworks
Familiarity with security and governance frameworks (e.g., ISO 27001, NIST)
Proven experience aiding customers with Cloud Enablement and familiarity with Microsoft’s Cloud Adoption Framework
Strategic thinker with hands-on technical expertise across both platform and AI disciplines
Effective in fostering and maintaining executive-level client relationships
Demonstrated ability to engage in senior-level technology decision-maker discussions related to agility, AI value, and business outcomes
Strong presentation, documentation, and analysis skills
Excellent communication and stakeholder management skills
Team player with proven leadership, communication, organizational, and interpersonal skills
Passionate about AI innovation and enterprise transformation
Comfortable navigating complex, multi-cloud environments
Microsoft Certified: Azure Solutions Architect Expert
Microsoft Certified: Azure AI Engineer Associate

Nice To Haves

Microsoft Azure DevOps Engineer Expert
TOGAF or other enterprise architecture certifications
ITIL Certifications

Responsibilities

Design and support client DevOps solutions and Public/Hybrid Cloud Architectures
Architect and support Azure Infrastructure environments, Development, and Testing environments
Scope complex projects based on business requirements and achievable benefits
Lead complex projects to completion on-time and on-budget
Architect solutions by mapping a customer’s business problem to an end-to-end technology solution
Create and deploy Terraform Templates and architect Infrastructure as Code (IaaC) solutions
Utilize and operate Azure DevOps pipelines and workflows
Build out systems and platforms to support scaling of existing environments, new applications, and initiatives, leveraging existing and new automation frameworks
Develop tools and processes to automate manual procedures and increase efficiency
Oversee continuous improvement and optimization of monitoring and analytics systems
Ensure adherence to production change control policies and identify opportunities for process improvement
Ensure infrastructure technology projects incorporate appropriate planning, technical analysis, budgets, and resource management to meet deadlines and objectives
Support Azure Migrate efforts — working with app teams to migrate custom and third-party applications to Azure
Develop high-level designs, technology assessments, technical architecture reviews, implementation/deployment schedules, disaster recovery, and business continuity planning
Architect end-to-end AI solutions using Azure services such as Azure OpenAI, Azure Machine Learning, Cognitive Services, and Azure Synapse Analytics
Define and implement scalable AI architectures that support real-time analytics, predictive modeling, and intelligent automation across client environments
Integrate AI models into enterprise applications, DevOps pipelines, and data pipelines to enhance operational outcomes
Establish and manage MLOps practices using Azure DevOps, Azure Kubernetes Service (AKS), and Azure Container Registry
Leverage AI tooling to augment DevOps automation, infrastructure monitoring, anomaly detection, and predictive capacity planning
Develop reusable AI architecture patterns and reference implementations for use across client engagements
Ensure AI systems meet performance, security, and compliance standards (including ISO 27001 and NIST frameworks)
Stay current with emerging AI technologies and Azure platform updates to continuously evolve service offerings
Lead technical design sessions and guide engineering teams through AI and platform implementation phases
Effectively facilitate meetings with senior management and executive stakeholders
Collaborate with clients as a trusted advisor to continuously improve IT Cloud Operations
Lead teams and cross-team meetings across practices
Provide technical mentorship to platform engineers, AI engineers, and developers
Develop strong executive-level client relationships and engage in senior-level technology decision-maker discussions related to agility, AI value, and business transformation