Solutions Architecture Lead (Applications Development Manager)

• Define and execute enterprise architecture and AI strategy aligned with business objectives.
• Lead solution architecture, application modernization, and AI-driven transformation initiatives.
• Design scalable, secure, and resilient cloud-native solutions.
• Evaluate AI vendors, platforms, open-source models, and third-party solutions.
• Develop technical roadmaps and long-term architecture strategies.
• Lead and mentor architects, software engineers, data scientists, and machine learning teams.
• Collaborate with business leaders to translate operational challenges into technical solutions.
• Present complex technical concepts, AI strategies, and ROI analyses to executive leadership.
• Manage architectural governance, risk assessment, compliance, and security standards.
• Oversee vendor relationships, budgeting, and technical contract negotiations.
• Drive Agile delivery practices and ensure successful project execution.

Note: Please do not submit candidates previously submitted to Posting 13917. Manager is seeking new resources only.

• Bachelor’s Degree in Computer Science, Computer Engineering, or related field.
• Minimum 3+ years of experience as a Lead managing technical employees and teams.
• Experience implementing and supporting AI/ML and Generative AI solutions.
• Experience with Agile methodologies.
• Hands-on experience with Jira and/or Azure DevOps.
• Strong leadership, communication, and stakeholder management skills.

Technical Knowledge

• Enterprise Architecture, Microservices, Distributed Systems, and API-First Design.
• Cloud Platforms including Azure, Salesforce, and GCP.
• AI/ML technologies including LLMs, SLMs, NLP, Computer Vision, Vector Databases, and RAG Architectures.
• Azure AI Studio and enterprise AI ecosystems.
• MLOps, CI/CD pipelines, Model Deployment, Monitoring, and Retraining.
• Data Engineering concepts including Data Lakes, Data Warehouses, and Data Pipelines.
• Security, Privacy, and AI Governance practices.
• CCPA, NIST AI RMF, EU AI Act, Data Residency, and Responsible AI principles.
• TOGAF, Zachman, and enterprise architecture frameworks.
• FinOps, Cloud Economics, GPU/TPU cost management, and AI consumption models.