Solutions Architect

Solution Architecture Manager – AI & Enterprise Architecture

Location: Phoenix, AZ (Local Candidates Only)

Contract: 7 months Duration

Work Arrangement: Hybrid – 4 Days per Week Onsite

Job Summary

We are seeking a Solution Architecture Manager to serve as a strategic, hands-on technical leader responsible for driving the next generation of enterprise systems. This role bridges traditional enterprise architecture with modern Artificial Intelligence, Machine Learning, and Generative AI technologies.

The ideal candidate will have strong experience designing modern, scalable, secure enterprise solutions and integrating AI capabilities into existing software ecosystems. This position requires a leader who can translate business requirements into technical strategies, guide cross-functional teams, and communicate complex architectural decisions to executive stakeholders.

Key Responsibilities

• Define and drive enterprise and solution architecture strategies aligned with business objectives.
• Design scalable, secure, resilient architectures using distributed systems, microservices, and API-first design .
• Develop and implement AI-centric enterprise solutions using LLMs, SLMs, NLP, computer vision, vector databases, and RAG architectures .
• Integrate AI/ML capabilities with existing enterprise applications, legacy systems, cloud platforms, and user interfaces.
• Evaluate AI vendors, open-source models, and third-party APIs to determine appropriate build vs. buy strategies.
• Establish technical roadmaps and long-term AI/architecture strategies aligned with organizational goals.
• Provide technical leadership, mentoring, and guidance to cloud architects, data scientists, ML engineers, and software development teams.
• Identify and mitigate technical, security, privacy, compliance, and ethical risks associated with AI implementations.
• Partner with business leaders, product teams, security, legal, and engineering stakeholders to drive architecture decisions and consensus.
• Evaluate architectural trade-offs, technology investments, and AI solutions based on scalability, security, performance, and ROI.
• Oversee cloud and AI cost optimization, including GPU/TPU compute and token-based AI API costs.
• Support budgeting, vendor management, technical contract evaluation, and technology procurement.
• Promote Agile/Scrum methodologies and modern engineering practices across technical teams.

Required Knowledge

• Enterprise and Cloud Architecture, including distributed systems, microservices, and API-first architecture .
• Major cloud platforms such as Salesforce, Microsoft Azure, and Google Cloud Platform (GCP) .
• Cloud-native AI/ML platforms and services, including Azure AI Studio .
• AI/ML and Generative AI ecosystems, including:
• Foundation Models
• LLMs and SLMs
• NLP
• Computer Vision
• Vector Databases
• RAG architectures
• MLOps, CI/CD, data pipelines, data lakes, data warehouses, model deployment, monitoring, and retraining.
• AI security, privacy, governance, and compliance.
• CCPA, NIST AI Risk Management Framework (AI RMF), EU AI Act , data residency, and responsible AI practices.
• AI risk mitigation techniques addressing bias, toxicity, hallucinations, and data privacy .
• Enterprise architecture frameworks such as TOGAF and Zachman .
• Agile/Scrum methodologies.
• Cloud economics and FinOps , including AI compute and token-based pricing models.

Required Skills & Abilities

• Strong ability to translate complex business requirements into practical, scalable, and cost-effective technical solutions.
• Excellent executive communication skills with the ability to present complex AI and architecture concepts to senior leadership and C-suite stakeholders.
• Strong risk identification and mitigation capabilities across technology, security, privacy, and AI governance.
• Ability to rapidly adapt to evolving AI technologies and apply emerging solutions to enterprise use cases.
• Strong cross-functional leadership and ability to influence stakeholders without relying solely on organizational authority.
• Strong collaboration skills across engineering, product, security, legal, data, and business teams.

Education

• Bachelor’s degree in Computer Science, Computer Engineering, or a related technical field.
• Equivalent combination of education and relevant professional experience may be considered.