Lead AI Architect

TechDigital Group; Charlotte (NC); On-site; USD 207,000 - 289,000; Full time

Job summary

TechDigital Group is seeking two experienced Lead Architects on a contract basis to strengthen delivery of architecture work across our technology portfolio. These roles operate at the Lead Architect level and partner closely with our internal architecture team, engineering leads, and business stakeholders.

The right candidates are hands-on, AI-fluent architects who can translate business and technical needs into architecture artifacts, prototype rapidly, and communicate trade-offs clearly to

Qualifications

• Hands-on AI experience building or integrating AI/GenAI/ML solutions.
• Proven ability to assemble architecture designs and documentation.
• Ability to drive rapid prototypes and POCs.
• Senior hands-on background with modern app, integration, and cloud patterns.
• Strong communication to technical and business stakeholders.
• Comfort operating across ambiguity to deliver outcomes quickly.

Responsibilities

• Assemble architecture designs and end-to-end artifacts.
• Apply AI capabilities and advise on patterns and trade-offs.
• Drive rapid prototypes and POCs to validate decisions.
• Partner with engineering, product, and business teams.
• Document and communicate designs clearly to all audiences.
• Uphold enterprise architecture standards and best practices.

Skills

AI & ML

Architecture design

Prototyping

Cloud patterns

Communication

Lead & mentoring

Python/Java

ADR documentation

Tools

Terraform

Docker

Kubernetes

REST/GraphQL

ArchiMate

Job description

Role Overview

We are seeking two experienced Lead Architects on a contract basis to strengthen delivery of architecture work across our technology portfolio. These roles operate at the Lead Architect level and partner closely with our internal architecture team, engineering leads, and business stakeholders.

The right candidates are hands‑on, AI‑fluent architects who can quickly translate business and technical needs into clear architecture artifacts and stand up working prototypes to prove out ideas fast. They should be comfortable moving between big‑picture design and rapid, tangible experimentation.

Key Responsibilities

• Assemble architecture designs — produce clear, end-to-end architecture artifacts: solution designs, reference architectures, diagrams, patterns, and architecture decision records.
• Apply AI capabilities — design and integrate AI / GenAI / machine-learning components into solutions, and advise on appropriate patterns, tooling, and trade-offs.
• Drive rapid prototypes — build quick proofs of concept and working prototypes to validate architecture decisions, de-risk options, and accelerate stakeholder alignment.
• Partner across teams — work with engineering, product, and business partners to align architecture with delivery goals and non-functional requirements (security, scalability, resilience, cost).
• Document and communicate — present designs and trade-offs clearly to both technical and non-technical audiences, and keep architecture documentation current and usable.
• Uphold standards — apply enterprise architecture standards, controls, and best practices throughout design and prototyping.

Required Qualifications (Must-Have)

• Demonstrable hands‑on AI experience — practical work building, integrating, or architecting AI / GenAI / ML solutions.
• Proven ability to put architecture details together — a track record of producing clear, complete architecture designs and documentation.
• Ability to drive quick prototypes — rapidly stand up POCs and working prototypes to test and demonstrate ideas.
• Senior, hands‑on technical background operating at a Lead Architect level, with strong design fundamentals across modern application, integration, and cloud patterns.
• Strong communication skills — able to explain architecture and trade-offs to technical teams and business stakeholders alike.
• Self-directed and comfortable working across ambiguity to deliver tangible outcomes quickly.

Technical Skills

Representative technical skills for these roles. Candidates should bring strong depth across several of these areas — tailor to our stack as needed:

• AI & Machine Learning — GenAI and large language models (LLMs), retrieval-augmented generation (RAG), agentic and prompt-engineering patterns, model APIs and integration, embeddings and vector stores; familiarity with common ML frameworks.
• Cloud & Platform — hands‑? experience with at least one major cloud (AWS, Azure, or GCP); containers and orchestration (Docker, Kubernetes); serverless services.
• Architecture & Integration — microservices, event-driven and API‑led design, REST / GraphQL APIs, messaging and streaming (e.g., Kafka), and enterprise integration patterns.
• Data & Information Architecture — data modeling, relational and NoSQL databases (strong SQL), data lakes / warehouses, ETL / ELT pipelines, and data governance / metadata.
• Languages & Prototyping — proficiency in Python and/or Java (or comparable); rapid prototyping, scripting, and notebook-based experimentation.
• Engineering Practices — CI/CD, infrastructure as code (e.g., Terraform), Git-based version control, and automated testing.
• Architecture Tooling — modeling and diagramming (C4, UML, or ArchiMate) and architecture decision records (ADRs).

Preferred Qualifications (Nice-to-Have)

• Depth in data / information architecture — experience designing data models, information flows, data platforms, or enterprise information architecture.
• Finance domain experience — prior work in Finance functions, especially Controllers / financial control and related processes.

What Success Looks Like

• Architecture artifacts and prototypes are delivered quickly and are clear enough to drive decisions.
• AI options are evaluated and applied pragmatically, with sound trade-off analysis.
• Stakeholders trust the designs and can act on them with minimal rework.

Notes for Sourcing

Please share this description with vendor partners to identify candidates who meet the must‑have criteria first, with preference given to those who also bring the data/information architecture and Finance (Controllers) experience noted above. Placeholders in the Role Snapshot (duration, start date, location, and rate band) should be completed before distribution.