AI Architect
About the role
The AI Architect at IFS is responsible for maintaining architectural coherence across GCS AI and Frictionless Time to Value (FTTV) initiatives. This senior lead-level individual contributor role involves participating in use-case and initiative shaping, reviewing proposed AI applications and FTTV solutions for alignment with strategy, and defining standards and reusable patterns. The architect collaborates closely with AI Engineering and FTTV stakeholders, ensuring solutions make appropriate use of existing knowledge, integrations, and services, and that specialist perspectives are incorporated early in the design process. The role requires significant experience in architecture across multiple applications or teams, practical experience with AI-enabled applications, and a strong understanding of modern software architecture and integration approaches. The company offers a flexible, hybrid work environment and values diversity, inclusion, and innovation.
Must have
- Significant experience in software, solution, application, integration, data, or AI architecture across multiple applications or engineering teams.
- Experience shaping technical solutions before implementation and assessing application boundaries, dependencies, integration points, and reuse opportunities.
- Practical experience with AI-enabled applications, including large language models, retrieval-based solutions, agentic systems, and structured and unstructured knowledge.
- Strong understanding of modern software architecture, APIs, distributed systems, cloud services, identity, security, and integration approaches.
- Experience defining architecture standards and reusable patterns collaboratively with engineers.
- Ability to identify duplication, hidden coupling, weak ownership models, and design choices that create long-term maintenance problems.
- Ability to evaluate and explain technical trade-offs to engineering, business, and leadership audiences.
- Ability to work through influence without relying on line authority and to distinguish portfolio-level concerns from engineering implementation decisions.
- Sufficient hands-on technical capability to prototype concepts, inspect implementations, and validate architectural assumptions when necessary.
- Sound judgment about when to decide, when to involve a specialist, and when to escalate an unresolved trade-off.
Nice to have
- Experience designing or reviewing enterprise AI applications in production.
- Experience with retrieval-augmented generation, agent architectures, shared knowledge services, evaluation frameworks, and AI observability.
- Experience with Azure AI services, Azure OpenAI, Azure AI Foundry, or comparable enterprise AI platforms.
- Experience with API-first, event-driven, microservice, and cloud-native solution patterns.
- Experience defining reusable components or platform capabilities across multiple teams.
- Experience with enterprise business applications, ERP, customer delivery, or service-delivery processes.
- Familiarity with GCS, FTTV, delivery tooling, and AI adoption priorities.
- Experience operating at Senior Lead, Principal, or equivalent individual-contributor level.
Technologies
- Agentic AI
- Azure
- Cloud Native
- ERP
- Event-Driven Architecture
- IFS
- LLM
- Microservices
- Observability
- OpenAI
- RAG
- Responsible AI
Highlights
IFS offers hybrid and flexible work opportunities to support diverse needs and lifestyles. The company emphasizes an inclusive workplace and a sense of community. No application deadline or specific application method is mentioned.
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