What success looks like in this role:
Design and lead the evolution of enterprise-wide AI platforms and architecture to enable AI-powered products, intelligent workflows, and scalable digital transformation. This role combines enterprise architecture, platform engineering, and AI delivery to build solutions that are secure, scalable, and operationally viable. The AI Platform Architect ensures end-to-end alignment from strategy through implementation, balancing innovation, governance, and enterprise usability.
Responsibilities:
- Define and drive enterprise architecture strategy across AI, data, cloud, and platform ecosystems
- Architect and evolve enterprise AI platforms, including LLM pipelines, RAG systems, and agentic workflows
- Design intelligent applications, copilots, and conversational AI solutions embedded into business processes
- Lead end-to-end solution architecture, from concept and prototyping through implementation and scale
- Develop target architectures, reusable patterns, and capability roadmaps for AI adoption
- Design and manage hybrid, multi-cloud, and on-prem infrastructure (AWS, Azure, GCP, GPU environments)
- Define and implement API strategy, integration patterns, and enterprise governance frameworks
- Establish DevSecOps practices, including CI/CD, Infrastructure as Code, and automated deployment pipelines
- Architect data platforms, knowledge systems, and analytics capabilities to enable AI and decision-making
- Enable enterprise integration across ERP, CRM, data platforms, and workflow systems
- Ensure security, compliance, and responsible AI practices aligned with regulatory requirements
- Lead hands-on prototyping and solution validation to accelerate delivery and reduce risk
- Provide senior stakeholder and board-level advisory on architecture decisions, risks, and trade-offs
- Drive vendor evaluation, technology selection, and AI tooling strategy
- Support and mentor engineering teams to ensure effective execution of architecture designs
What You Bring
Enterprise Architecture & Platform Strategy
- Strong experience in enterprise and solution architecture across complex environments
- Ability to define architecture principles, governance models, and long-term technology strategy
- Expertise in platform thinking and enterprise system design
AI & Data Platforms
- Experience with AI/ML platforms, including LLMs, RAG, semantic search, and agent-based systems
- Understanding of AI-enabled workflows, knowledge systems, and enterprise AI adoption
- Ability to design scalable, production-grade AI platforms
Cloud, Infrastructure & Engineering
- Strong foundation in cloud (AWS, Azure, GCP), hybrid, and on-prem architectures
- Experience with GPU infrastructure, model deployment, and inference optimization
- Proficiency in APIs (REST, GraphQL), microservices, and distributed systems
- Hands-on experience with DevSecOps, CI/CD pipelines, and Infrastructure as Code (Terraform)
Data, Integration & Security
- Knowledge of data platforms, ETL, data warehousing, and analytics systems
- Expertise in enterprise integration patterns and API governance
- Strong understanding of security, identity (SSO, OAuth2/OIDC), and compliance frameworks (ISO27001, GDPR, etc.)
Leadership & Collaboration
- Ability to influence senior stakeholders and cross-functional teams
- Strong communication translating technical architecture into business outcomes
- Experience leading engineering and architecture teams
- Balanced approach to innovation, governance, cost, and scalability
Ideal Background
- Proven experience as an Enterprise Architect, AI Platform Architect, or Solution Architect
- Track record delivering large-scale AI, data, and cloud transformation programs
- Experience designing and implementing enterprise AI platforms and intelligent applications
- Strong mix of strategic thinking and hands-on architecture execution
- Experience working in complex, multi-stakeholder and regulated environments
- Background in enterprise systems integration (ERP, CRM, data platforms, digital ecosystems)
- Demonstrated ability to balance innovation with operational stability, risk, and compliance
#LI-SS1
You will be successful in this role if you have:
- 12+ years of experience in software engineering, AI/ML systems, or platform architecture, with strong focus on Generative AI
- Proven experience acting as Senior Principal / Enterprise Technical Architect within large Engineering organizations
- Demonstrated ability to define architecture standards and guide large engineering teams
- Strong stakeholder engagement skills across engineering leadership and executive teams
- Self-driven, collaborative, and comfortable working in fast-paced engineering environments
- Bachelor’s or Master’s degree in Computer Science, Engineering, AI, or related field
- Cloud or AI certifications (Azure Developer, Azure AI Engineer, or equivalent) preferred
Unisys is proud to be an equal opportunity employer that considers all qualified applicants without regard to age, blood type, caste, citizenship, color, disability, family medical history, family status, ethnicity, gender, gender expression, gender identity, genetic information, marital status, national origin, parental status, pregnancy, race, religion, sex, sexual orientation, transgender status, veteran status or any other category protected by law.
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