Job Description
Solutions Architecture Lead (Apps Dev Manager)
7 Months
Phoenix, AZ
Hybrid 4 days a week. Local ONLY.
As the Solution Architecture Manager, you will be a strategic, dual-focus technical leader driving our next generation of enterprise systems. In this highly visible role, you will bridge the gap between traditional enterprise architecture and the rapidly evolving landscape of artificial intelligence. You will not just oversee systems; you will be responsible for building modern, scalable software solutions with AI at their core.
Knowledge:
Enterprise & Cloud Architecture: Deep understanding of distributed systems, microservices, API-first design, and major cloud platforms (Salesforce, Azure, GCP), including their native AI/ML stacks (e.g. Azure AI Studio).
AI/ML & Generative AI Ecosystems: Comprehensive knowledge of the AI lifecycle, Foundation Models (LLMs, SLMs), Natural Language Processing (NLP), computer vision, vector databases, and retrieval-augmented generation (RAG) architectures.
MLOps & Data Engineering: Understanding of CI/CD for machine learning (MLOps), data pipelines, data lakes/warehouses, and model deployment, monitoring, and retraining strategies.
Security, Privacy & AI Ethics: Knowledge of data privacy regulations (CCPA), AI compliance frameworks (NIST AI RMF, EU AI Act), data residency, and techniques for mitigating AI bias, toxicity, and hallucinations.
Architecture Frameworks & Methodologies: Familiarity with standard architectural frameworks (e.g., TOGAF, Zachman) and Agile/Scrum project management methodologies.
FinOps & Cloud Economics: Understanding of cloud cost management, particularly the cost structures associated with AI compute (GPUs, TPUs) and API token-based pricing models.
Abilities
Innate or acquired capacities to perform tasks and handle scenarios.
Business-to-Technical Translation: The ability to listen to non-technical business stakeholders, identify operational bottlenecks, and translate those needs into viable, cost-effective AI and architectural solutions.
Executive Communication: The ability to articulate complex AI concepts, architectural trade-offs, and ROI to C-suite executives and board members clearly and persuasively.
Risk Anticipation & Mitigation: The ability to foresee technical, security, or ethical risks in AI deployments and proactively design safeguards (e.g., human-in-the-loop workflows, data masking).
Adaptability & Continuous Learning: The ability to pivot rapidly in response to the fast-paced evolution of AI technologies, continuously absorbing new research and applying it to enterprise challenges.
Cross-Functional Influence: The ability to lead by influence rather than just authority, driving consensus among product managers, legal teams, security officers, and engineering leads to ensure smooth deployment of AI services.
Bachelors in Computer Science or Computer Engineering
Proficiencies and techniques developed through training and experience.
System Design & Integration: Skill in designing scalable, secure, and resilient architectures that seamlessly integrate AI models into existing enterprise software, legacy systems, and user interfaces.
Technical Evaluation & Prototyping: Proficiency in assessing vendor AI solutions, open-source models (e.g., Hugging Face), and third-party APIs to determine the best build vs. buy approach for business use cases.
Technical Leadership & Mentoring: Skill in managing, coaching, and evaluating cross-functional technical teams, including cloud architects, data scientists, machine learning engineers, and software developers.
Strategic Roadmapping: Skill in creating and maintaining a technical vision and multi-year AI/architecture roadmap that aligns with the broader business objectives.
Budgeting & Vendor Management: Skill in negotiating technical contracts, managing software vendor relationships, and optimizing departmental and project budgets.
Software Development (High-Level): Foundational skill in relevant programming languages (e.g., Python, SQL, Java, or Go) to effectively review architecture, guide engineering teams, and troubleshoot complex integrations.
Required Skills
At least 3+ years as a Lead experience managing employees
AI experience
Jira or Devops experience
Agile Methodology
Preferred Skills
TOGAF
Product Management
7 Months
Phoenix, AZ
Hybrid 4 days a week. Local ONLY.
As the Solution Architecture Manager, you will be a strategic, dual-focus technical leader driving our next generation of enterprise systems. In this highly visible role, you will bridge the gap between traditional enterprise architecture and the rapidly evolving landscape of artificial intelligence. You will not just oversee systems; you will be responsible for building modern, scalable software solutions with AI at their core.
Knowledge:
Enterprise & Cloud Architecture: Deep understanding of distributed systems, microservices, API-first design, and major cloud platforms (Salesforce, Azure, GCP), including their native AI/ML stacks (e.g. Azure AI Studio).
AI/ML & Generative AI Ecosystems: Comprehensive knowledge of the AI lifecycle, Foundation Models (LLMs, SLMs), Natural Language Processing (NLP), computer vision, vector databases, and retrieval-augmented generation (RAG) architectures.
MLOps & Data Engineering: Understanding of CI/CD for machine learning (MLOps), data pipelines, data lakes/warehouses, and model deployment, monitoring, and retraining strategies.
Security, Privacy & AI Ethics: Knowledge of data privacy regulations (CCPA), AI compliance frameworks (NIST AI RMF, EU AI Act), data residency, and techniques for mitigating AI bias, toxicity, and hallucinations.
Architecture Frameworks & Methodologies: Familiarity with standard architectural frameworks (e.g., TOGAF, Zachman) and Agile/Scrum project management methodologies.
FinOps & Cloud Economics: Understanding of cloud cost management, particularly the cost structures associated with AI compute (GPUs, TPUs) and API token-based pricing models.
Abilities
Innate or acquired capacities to perform tasks and handle scenarios.
Business-to-Technical Translation: The ability to listen to non-technical business stakeholders, identify operational bottlenecks, and translate those needs into viable, cost-effective AI and architectural solutions.
Executive Communication: The ability to articulate complex AI concepts, architectural trade-offs, and ROI to C-suite executives and board members clearly and persuasively.
Risk Anticipation & Mitigation: The ability to foresee technical, security, or ethical risks in AI deployments and proactively design safeguards (e.g., human-in-the-loop workflows, data masking).
Adaptability & Continuous Learning: The ability to pivot rapidly in response to the fast-paced evolution of AI technologies, continuously absorbing new research and applying it to enterprise challenges.
Cross-Functional Influence: The ability to lead by influence rather than just authority, driving consensus among product managers, legal teams, security officers, and engineering leads to ensure smooth deployment of AI services.
Bachelors in Computer Science or Computer Engineering
Proficiencies and techniques developed through training and experience.
System Design & Integration: Skill in designing scalable, secure, and resilient architectures that seamlessly integrate AI models into existing enterprise software, legacy systems, and user interfaces.
Technical Evaluation & Prototyping: Proficiency in assessing vendor AI solutions, open-source models (e.g., Hugging Face), and third-party APIs to determine the best build vs. buy approach for business use cases.
Technical Leadership & Mentoring: Skill in managing, coaching, and evaluating cross-functional technical teams, including cloud architects, data scientists, machine learning engineers, and software developers.
Strategic Roadmapping: Skill in creating and maintaining a technical vision and multi-year AI/architecture roadmap that aligns with the broader business objectives.
Budgeting & Vendor Management: Skill in negotiating technical contracts, managing software vendor relationships, and optimizing departmental and project budgets.
Software Development (High-Level): Foundational skill in relevant programming languages (e.g., Python, SQL, Java, or Go) to effectively review architecture, guide engineering teams, and troubleshoot complex integrations.
Required Skills
At least 3+ years as a Lead experience managing employees
AI experience
Jira or Devops experience
Agile Methodology
Preferred Skills
TOGAF
Product Management
Numbers & Facts
| Location | Phoenix, AZ |
| Industry | Staffing/Employment Agencies |
| Company Size | 100 to 499 employees |
| Year Founded | 1990 |
| Website | http://www.sunrisesys.com/ |
About Company
Sunrise Systems was founded in 1990 with a clear vision to deliver world-class staffing service solutions in all labor categories, including IT consulting and solutions; all with the commitment to provide service that exceeds expectations and become the most trusted name in the industry. More than two and a half decades later, we pride ourselves on being at the forefront of the staffing industry. Combining our deep industry expertise, insights, and global resources, we have partnered with our clients to connect them with top professionals across several different industries.
We provide cost-effective Managed Staffing Solutions, Information Technology and Information Technology Consulting Services to several Fortune 500 companies and U.S. Government agencies. We provide our clients with flexible engagement models and customized products that are budget and time specific. Understanding the challenges that every business faces, we offer our services either on-site at the clients' site or from one of our globally distributed technology centers. Our onshore and offshore development capabilities ensure that we excel at meeting customer requirements every single time.
Our collective business experience spans over two and a half decades and ranges from:
- Business, management, and technical fields
- Information technology consulting and software solutions.
- Providing strategic support for the development and long-term growth of new business ventures across several industries including but not limited to; accounting, banking, finance, and recruitment.
- Motivating technology staff and establishing partnerships with Fortune 500 companies
Sunrise Systems has a vast range of competence in:
- Design, development, and support of cloud-based solutions from simple to highly complexed
- Database administration of multi-platform applications, complex databases, and web-based environments that include all aspects of installation, planning, maintenance, and monitoring.
- Data processing and data migration
- Application re-engineering and platform migration
- Working with the Information Systems and end-user communities at all levels to resolve issues and establish consensus.
Skills
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