AI Domain Architect

Allegis Global Solutions•Hanover, MD

23h•Remote

About The Position

Working at Allegis Global Solutions (AGS) is a career within a community that invests in your development and empowers you to make a measurable impact. AGS helps companies worldwide transform their people into a competitive advantage by designing workforces to meet missions and unleash human enterprise. They offer global services including permanent and extended workforce management, services procurement, consulting, direct sourcing, and their Universal Workforce Model™. AGS operates in over 100 countries, providing exposure to diverse cultures and global markets. The AI Domain Architect is a senior enterprise architecture role responsible for designing and operationalizing AI-enabled solutions across assigned domains and delivery portfolios. This role bridges enterprise AI strategy and practical execution, translating reference architectures, governance requirements, and platform capabilities into scalable, production-ready solution designs embedded within delivery teams. Operating at the enterprise level, the AI Domain Architect influences architectural direction across multiple initiatives, partnering with engineering, product, governance, and platform stakeholders to ensure AI systems are secure, observable, cost-effective, and aligned with AGS standards. This is not a purely advisory role; the AI Domain Architect works directly with AI Product, Engineering, and delivery teams to ensure designs move successfully from concept to production.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent experience
8–12+ years of experience in enterprise architecture, solution architecture, platform engineering, or AI-enabled system design
Demonstrated experience designing and implementing production-grade AI or automation solutions
Strong understanding of AI system design patterns including orchestration, tool-use integration, evaluation approaches, and operational considerations
Experience with secure integration practices (identity, access controls, audit logging, observability)
Proven ability to operate at enterprise scope while remaining delivery-oriented
Comfortable with light-weight hands-on validation, prototyping, or technical design deep-dives
Strong stakeholder communication skills with ability to translate architectural concepts into actionable delivery guidance

Nice To Haves

Experience operating in regulated or high-governance environments
Familiarity with AI platform capabilities, MLOps practices, and production monitoring
Experience within staffing, workforce solutions, HR technology, or AI-enabled operating models
Prior experience supporting multiple delivery teams within a COE or enterprise architecture function

Responsibilities

Design AI-enabled architecture across domains, ensuring alignment with enterprise standards and platform capabilities
Translate enterprise reference patterns into domain-level implementation blueprints
Guide architecture decisions for agentic systems, orchestration workflows, model integration, and AI-enabled capabilities
Ensure secure integration patterns including identity, permissions, auditability, and service-to-service authentication
Partner with engineering leads to ensure scalable and maintainable implementations
Embed observability, telemetry, evaluation, and monitoring requirements into AI system designs
Ensure AI solutions are built with lifecycle management, versioning, cost monitoring, and safe deployment practices
Implement evaluation frameworks including baseline test sets, regression validation, and quality thresholds
Collaborate with AI Product, Engineering, and Delivery teams to integrate logging, safety signals, and performance metrics
Support production readiness reviews and architectural risk assessments
Translate governance and risk requirements into practical architectural controls
Ensure required documentation, evidence, and compliance checkpoints are incorporated into delivery workflows
Guide teams through architecture reviews and governance intake processes
Embed approved guardrails and platform controls into solution designs
Proactively identify architectural risks and propose mitigation strategies
Promote reuse of approved templates, patterns, and reference implementations
Identify duplication risks within the domain and recommend consolidation strategies
Provide feedback to enterprise architecture and platform teams to refine reusable assets
Contribute to evolving standards based on implementation learnings and post-production insights
Operate as a senior architectural advisor across engineering, product, governance, and domain leadership
Participate in technical design workshops and delivery planning sessions
Provide architectural due diligence for AI-enabled integrations and third-party solutions
Support roadmap planning by ensuring architectural feasibility and scalability considerations