AI Architect | Digital Products & AI

PA Consulting•Charlotte, NC

1d•Hybrid

About The Position

As an AI Architect on the Digital Products & AI team, you will work directly with clients to shape, design, and lead delivery of digital products, AI agents, intelligent workflows, and modernized platforms. You will own delivery architecture for complex engagements, translate business problems into executable solutions, and keep implementation aligned with the design. You may help shape opportunities before delivery and, on some engagements, remain involved in operating products after go-live. This is a hands-on architecture and engineering role in which AI agents produce much of the code. You will define architecture, controls, and acceptance criteria; make technical decisions that hold up in production and with client technology leaders; and help teams navigate ambiguity while moving delivery forward. The practice uses small senior teams to deliver production solutions in short timeframes, rather than pilots or demos. The role includes working with Product Strategists and AI Engineers to design solutions, build agentic-system components, modernize platforms around current business needs, and create reusable patterns and tooling. The company offers a hybrid arrangement, with work in an office or at a client site at least two days per week; assignments may require up to five days per week on a client site.

Requirements

Track record of designing, building, and delivering complex technology solutions in production environments.
Experience leading architecture and technical delivery for complex software, cloud, or digital transformation initiatives while continuing to build and operate production software.
Strong software engineering skills, ideally including Python and TypeScript.
Experience designing and delivering cloud-native systems on AWS, Azure, or GCP.
Hands-on experience building AI applications and agent-based systems in production.
Experience with orchestration frameworks such as LangChain, LangGraph, LlamaIndex, or similar, and judgment about when an orchestration layer merits its complexity.
Experience building retrieval-enabled systems and working with technologies such as pgvector, Elasticsearch, or OpenSearch; understanding of trade-offs among retrieval quality, latency, and cost.
Experience integrating applications with enterprise systems, data platforms, APIs, identity providers, and MCP-enabled services.
Experience owning solution architecture for complex technology initiatives, including decomposition, sequencing, and technical decisions across delivery teams.
Strong technical judgment and communication skills, and ability to navigate ambiguity while working with clients and multidisciplinary teams and balancing speed with quality, security, and maintainability.
Experience working directly with senior technology stakeholders and credibility discussing solution approaches with engineering leaders and client CTOs.

Nice To Haves

Experience delivering solutions in consulting or professional services, or experience as a technical founder.
Experience in healthcare and life sciences, manufacturing, energy and utilities, transportation, or consumer industries.
Experience building reusable platforms, tooling, or AI solutions in regulated environments.

Responsibilities

Own delivery architecture for digital products, AI agents, intelligent workflows, and modernization initiatives, maintaining alignment from discovery through deployment.
Architect production-critical AI elements, including tool selection, memory and context management, guardrails, and human-in-the-loop controls.
Define, build, and guide implementation of agentic-system components, including retrieval pipelines, MCP services and integrations, and systems connecting AI capabilities to enterprise data and processes at scale.
Modernize platforms and applications around current business needs, rebuilding where necessary rather than merely moving legacy functionality to newer technology.
Design security and operational resilience into solutions, including access controls, identity management, deployment guardrails, and oversight of automated actions.
Break complex problems into deliverable components by defining scope, sequencing, implementation approaches, and delivery plans, and assessing feasibility and technical risk.
Create reusable patterns, approaches, and tooling that strengthen future engagements and may become market-facing capabilities and products.
Work directly with clients and multidisciplinary teams, helping shape opportunities and guide delivery through implementation.