AI Solution Architecture Manager

LanceSoft, Inc.; Phoenix (AZ); On-site; USD 140,000 - 210,000; Full time

Job summary

Lancesoft is seeking a Solution Architecture Manager to serve as a strategic technical leader bridging enterprise architecture with AI and Generative AI. You will design scalable, secure enterprise systems and lead cross-functional teams, aligning technology with business goals and regulatory requirements.

The role focuses on delivering AI-enabled solutions across cloud, data, ML, and AI governance. You will manage roadmaps, evaluate vendors and platforms, and mentor architects, developers, and

Qualifications

• Bachelor's degree in a technical field.
• 3+ years in a lead/management role.
• Experience with AI/Generative AI.
• Experience with Jira or Azure DevOps.
• Strong Agile experience.
• Enterprise architecture and system design.

Responsibilities

• Lead the design and evolution of scalable, secure enterprise architectures.
• Develop AI-enabled solutions using cloud, data, ML, and Generative AI tech.
• Translate business needs into technical AI solutions.
• Evaluate AI platforms, vendors, and APIs for build-vs-buy decisions.
• Develop and maintain multi-year technology and AI roadmaps.
• Partner with cross-functional teams to deliver solutions.
• Identify and mitigate technical, security, privacy, and AI risks.
• Provide mentorship to architects, developers, and data scientists.
• Communicate architecture and ROI to senior leadership.
• Manage vendors, contracts, budgets, and cloud/AI costs.
• Ensure alignment with Agile/Scrum and EA standards.

Skills

Enterprise Architecture

Cloud Architecture

AI/ML

Generative AI

TOGAF

Zachman

MLOps

Security & Compliance

Budgeting/FinOps

Python

SQL

Java

Go

Communication

Leadership

Vendor Management

Jira

Azure DevOps

Education

Bachelor's degree in Computer Science/Computer Engineering

Tools

Jira

Azure DevOps

Job description

We are seeking a Solution Architecture Manager to serve as a strategic, dual-focus technical leader responsible for driving the next generation of enterprise systems. This highly visible role will bridge traditional enterprise architecture with the rapidly evolving landscape of Artificial Intelligence and Generative AI.

The ideal candidate will have strong experience designing modern, scalable, secure enterprise solutions and the leadership skills to guide cross-functional technical teams. This individual will play a key role in integrating AI capabilities into enterprise applications while ensuring alignment with business objectives, security requirements, compliance standards, and cost considerations.

Key Responsibilities

• Lead the design and evolution of scalable, secure, and resilient enterprise architectures.
• Develop AI-enabled solutions using modern cloud, data, machine learning, and Generative AI technologies.
• Translate business requirements and operational challenges into practical technical and AI solutions.
• Evaluate AI platforms, vendors, open-source models, and third-party APIs to support build-vs-buy decisions.
• Develop and maintain multi-year technology and AI architecture roadmaps.
• Partner with engineering, product, data science, security, legal, and business teams to drive successful solution delivery.
• Identify and mitigate technical, security, privacy, compliance, and AI-related risks.
• Provide technical leadership, mentoring, and guidance to architects, developers, data scientists, and machine learning engineers.
• Communicate complex architecture, AI concepts, technical trade-offs, risks, and ROI to senior leadership.
• Manage technology vendors, technical contracts, budgets, and cloud/AI costs.
• Ensure solutions follow Agile/Scrum methodologies and enterprise architecture standards.

Required Knowledge

• Enterprise and Cloud Architecture, including distributed systems, microservices, API-first design, and major cloud platforms such as Azure, GCP, and Salesforce.
• AI/ML and Generative AI ecosystems, including:
• LLMs / SLMs
• NLP
• Computer Vision
• Vector Databases
• Retrieval-Augmented Generation (RAG)
• MLOps and Data Engineering, including CI/CD, data pipelines, data lakes/warehouses, model deployment, monitoring, and retraining.
• AI security, privacy, governance, and compliance, including CCPA, NIST AI RMF, EU AI Act, data residency, AI bias, toxicity, and hallucination mitigation.
• Enterprise architecture frameworks such as TOGAF and Zachman.
• Cloud economics and FinOps, including AI compute costs, GPU/TPU usage, and API/token-based pricing.

Required Abilities & Skills

• Ability to translate complex business requirements into scalable, cost-effective technical and AI solutions.
• Strong executive communication skills with the ability to explain complex technical concepts and architectural trade-offs to senior leadership.
• Ability to anticipate technical, security, privacy, and ethical risks and implement appropriate safeguards.
• Ability to adapt quickly to emerging AI technologies and apply new solutions to enterprise challenges.
• Strong cross-functional leadership and stakeholder management skills.
• Expertise in designing scalable, secure, and resilient architectures integrating AI with enterprise and legacy systems.
• Experience evaluating AI vendors, open-source models such as Hugging Face, and third-party APIs.
• Strong technical leadership, team management, coaching, and mentoring capabilities.
• Experience developing strategic technology and AI roadmaps.
• Experience with budgeting, vendor management, and technical contract negotiations.
• Foundational knowledge of programming languages such as Python, SQL, Java, or Go.

Minimum Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or a related technical field.
• 3+ years of experience in a lead/management role with responsibility for managing employees.
• Professional experience working with Artificial Intelligence / Generative AI technologies.
• Experience with Jira or Azure DevOps.
• Strong understanding and practical experience with Agile methodologies.
• Strong enterprise architecture and system design experience.

Preferred Qualifications

• TOGAF certification or experience.
• Experience leading enterprise-wide AI transformation initiatives.
• Experience working with cloud-native AI/ML platforms and MLOps environments.