Why Join PPC
PPC is a mission-driven organization grounded in servant leadership, strong values, and a commitment to supporting the people and communities it serves. This role offers the opportunity to help shape how AI is thoughtfully designed, governed, and scaled across a growing family of companies. It is a meaningful opportunity to build enterprise capability, influence strategy, and make a practical impact in a value-led organization.
Job Description Summary
Role, Function & Organization
PPC is seeking a Lead AI Architect to design and operationalize scalable enterprise AI capabilities across a multi-company construction and infrastructure services organization. Reporting to the Director, AI Strategy and Enablement, this role will translate AI strategy, product priorities, and business needs into secure architectures, reusable platform capabilities, and production-ready AI solutions.
This is a hands-on architecture role for someone who can shape technical direction, build prototypes and reference implementations, evaluate platforms and vendors, and guide delivery as PPC's AI portfolio grows.
Initial focus areas include Microsoft 365 Copilot, Copilot Studio agents, intelligent automation, enterprise search, knowledge-grounded AI, data-enabled AI solutions, adoption insights, cost visibility, enablement reporting, and continuous improvement.
At PPC Partners we believe in the Power to Serve along with the Pursuit of Excellence. As such the following values guide our behaviors: A Servant's Heart -- Focus on the Needs of Others, Wisdom -- Insightful, Integrity -- Honesty and Trustworthy, Courage -- Decisive and Confident in Others, Humility -- Modest and Respectful, Passion -- Unfailing Dedication
Essential Duties and Responsibilities
Architecture & Standards:
- Lead enterprise AI architecture, solution design, technical standards, and reusable patterns for AI-enabled applications, agents, automation, RAG, enterprise search, and integrations
Solution Delivery:
- Translate business needs and product priorities into scalable architectures, implementation plans, prototypes, reference implementations, and production-ready solutions
Platform & Governance:
- Establish secure, measurable, and supportable practices for identity, access, telemetry, evaluation, cost visibility, DevOps, LLMOps, release, and support
Partnership & Technical Leadership:
- Collaborate with AI Strategy and Enablement, product management, IT, cybersecurity, BI/data teams, business stakeholders, vendors, and delivery partners while mentoring technical contributors
Required Qualifications
- Experience and education: Bachelor's degree in Computer Science, Information Systems, Engineering, Technology, or a related field, or equivalent experience; 12+ years of experience designing, developing, and delivering enterprise software, cloud platforms, or complex business applications; 7+ years of experience in software, solution, cloud, or enterprise architecture; and 5+ years of hands-on engineering experience
- Cloud, AI, and platform architecture: 5+ years of cloud architecture and development experience with Azure or a comparable platform, plus 3+ years designing, building, deploying, or supporting production AI-enabled applications, generative AI solutions, assistants, agents, intelligent automation, RAG, enterprise search, or knowledge-grounded AI capabilities.
- Enterprise solution design: Experience designing scalable applications, APIs, integrations, cloud-native services, connected systems, reusable technical patterns, and AI architecture patterns for orchestration, identity, evaluation, telemetry, cost visibility, auditability, and operational support.
- Delivery, governance, and data integration: Experience applying secure coding, automated testing, CI/CD, DevOps, LLMOps, AI evaluation, release management, observability, and production support, including solutions that integrate enterprise data, documents, search indexes, governed content, semantic models, or cloud data environments.
- Business partnership and leadership: Ability to translate business requirements and product priorities into technical designs, feasibility assessments, estimates, platform evaluations, and buy-versus-build recommendations while communicating effectively with business leaders, users, developers, IT, cybersecurity, BI/data teams, vendors, and partners.
Preferred Qualifications
- Experience with Snowflake, cloud data platforms, semantic layers, data products, analytics engineering, or modern enterprise data architectures.
- Experience building AI-enabled applications or services using Python, TypeScript, .NET, or modern AI application frameworks.
- Experience with vector databases, embeddings, hybrid search, reranking, or retrieval optimization for RAG and knowledge-grounded AI solutions.
- Experience designing agent for orchestration, tool use, function calling, workflow integration, or multi-agent patterns.
- Experience implementing responsible AI technical controls, guardrails, red-teaming, model evaluation, prompt testing, or safety and quality assurance practices.
- Hands-on experience with API management, integration platforms, workflow orchestration, or automation platforms that connect AI capabilities with enterprise systems.
- Experience in construction, infrastructure services, industrial services, field operations, or similarly distributed business environments.