AI Architect - Digital Products & AI

Paconsulting; Charlotte (NC); On-site; USD 180,000 - 240,000; Full time

Job summary

Paconsulting seeks an AI Architect to lead delivery of digital products, AI agents, and intelligent workflows. You will design and own the delivery architecture for complex engagements and translate business problems into executable solutions.

Working with Product Strategists and AI Engineers, you will ensure alignment from discovery through deployment. This hands-on role emphasizes strong engineering judgment and production-ready patterns.

Qualifications

• Architectural and delivery leadership experience for complex software or digital transformation initiatives.
• Hands-on software engineering with production systems in cloud environments.
• Experience building AI applications and agent-based systems in production.
• Familiarity with AI orchestration frameworks and decision-making around complexity.
• Experience integrating applications with enterprise data platforms and APIs.

Responsibilities

• Own the delivery architecture for digital products, AI agents, and modernization initiatives.
• Architect the elements that determine production success, including tool choice and guardrails.
• Define and guide implementation of components powering agentic systems and data integrations.
• Modernize platforms and applications to meet current business needs.
• Design security and operational resilience into solutions from the start.
• Break down complex problems into deliverable components with clear scope and risk.

Skills

Architecture foundations

Software engineering

Python

TypeScript

Cloud-native systems

AWS/Azure/GCP

AI engineering

LangChain/LangGraph

Retrieval systems

Systems integration

Technical judgment

Tools

pgvector

Elasticsearch/OpenSearch

Job description

This practice is built for the way enterprise software actually gets made now: small senior pods, AI agents doing much of the build, and outcomes in weeks where traditional delivery approaches took months. We build digital products, AI agents, intelligent workflows and modernised platforms that help organizations operate differently across healthcare and life sciences, manufacturing, energy and utilities, transportation and consumer industries. None of it is pilots or demos. The solutions we build run in production and solve problems that matter to our clients' businesses.

As an AI Architect, you'll work directly with clients to shape, design, and lead the delivery of those solutions. Working alongside Product Strategists and AI Engineers, you'll own the delivery architecture for complex engagements, translating business problems into executable solutions and ensuring what gets built remains aligned to what was designed. You'll help shape opportunities before delivery begins and stay close to them throughout implementation. On some engagements, we continue to run what we've built, giving you the opportunity to stay close to the product and see the impact of your work long after go‑live.

This is a hands‑on architecture and engineering role. Most of the code here is written by agents. That does not make this a supervision job. It moves the engineering upstream, where strong engineering judgment becomes even more important. You'll define the architecture, controls, and acceptance criteria that determine whether a solution succeeds in production, while helping teams navigate ambiguity and move delivery forward. You'll be expected to make technical decisions that stand up not only in delivery, but also in front of client technology leaders who will ultimately be accountable for the outcome. Requirements do not always arrive fully formed, and part of the role is helping define the problem while continuing to move delivery forward.

As part of the Digital Products & AI team, you can expect to:

• Own the delivery architecture for digital products, AI agents, intelligent workflows, and modernisation initiatives, ensuring solutions remain aligned from discovery through deployment.
• Architect the elements that determine whether AI solutions succeed in production, including tool selection, memory and context management, guardrail design, and human‑in‑the‑loop controls.
• Define, build, and guide the implementation of the technical components that power agentic systems, including retrieval pipelines, MCP services and integrations, and the systems that connect AI capabilities to enterprise data and processes at scale.
• Modernise platforms and applications around current business needs, rebuilding where necessary rather than simply moving legacy functionality onto newer technology.
• Design security and operational resilience into solutions from the start, including access controls, identity management, deployment guardrails, and oversight of automated actions.
• Break down complex problems into deliverable components, defining scope, sequencing, implementation approaches, and delivery plans while determining feasibility and technical risk.
• Create reusable patterns, approaches, and tooling that strengthen future engagements, with the strongest ideas becoming capabilities and products we take to market.

You have a track record of designing, building, and delivering complex technology solutions in production environments. While our delivery model may be new to you, we'll bring you up to speed on how we plan, execute, and assure our work.

To be successful, you'll have:

• Architecture and engineering foundations Experience leading architecture and technical delivery for complex software, cloud, or digital transformation initiatives while still building and operating production software.
• Strong software engineering skills, ideally including Python and TypeScript.
• Experience designing and delivering cloud‑native systems on AWS, Azure, or GCP.
• AI engineering Hands‑on experience building AI applications and agent‑based systems in production. Experience with orchestration frameworks such as LangChain, LangGraph, LlamaIndex, or similar technologies, and the judgment to know when an orchestration layer earns its complexity.
• Experience building retrieval‑enabled systems and working with technologies such as pgvector, Elasticsearch, or OpenSearch, with an understanding of the trade‑offs between retrieval quality, latency, and cost.
• Architecture and delivery leadership 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 decision‑making across delivery teams.
• Strong technical judgment, communication skills, and the ability to navigate ambiguity while working directly with clients and multidisciplinary teams, balancing delivery speed wit