We are seeking an experienced AI Architect to join our Architecture & Technology Board and drive scalable, responsible AI adoption across Service Delivery. In this role, you will define architectural standards, governance frameworks, and reusable patterns that enable teams to build secure, production-ready AI solutions aligned with enterprise objectives.
Define and govern architecture standards, patterns, and guardrails for AI/ML, GenAI, and data platforms.
Evaluate and approve AI solutions through the Architecture & Technology Forum.
Ensure alignment with enterprise architecture, data governance, security, and compliance requirements.
Guide adoption of advanced AI capabilities, including MCP, A2A communication, AI Gateways, and observability frameworks.
Oversee production-grade AI deployments to ensure scalability, reliability, and operational excellence.
Establish best practices for data quality, lineage, governance, compliance, and lifecycle management.
Maintain baseline architectures for AI services, platforms, and data ecosystems.
Assess business use cases for AI applicability, technical feasibility, and business value.
Advise engineering teams on optimal solutions across AI, automation, and traditional software approaches.
Promote reusable AI components, datasets, integration patterns, and architecture standards.
Drive adoption of modern architecture patterns, data flows, and enterprise integration strategies.
Evaluate emerging technologies and define AI adoption roadmaps for Service Delivery.
Publish architectural guidelines, whitepapers, and thought leadership content.
Collaborate with Ericsson architecture and innovation teams to align initiatives, share knowledge, and accelerate reuse.
Act as the technical bridge between global AI initiatives and Service Delivery execution.
Strong AI/ML architecture experience with prior hands-on AI application development of 8 + years.
Proven experience leading or governing enterprise-scale AI/ML deployments.
Deep expertise in GenAI, LLMs, RAG architectures, and enterprise AI solution patterns.
Strong understanding of data modeling, ETL/ELT pipelines, data engineering, governance, lineage, and compliance.
Experience with data lakes, data warehouses, streaming platforms, feature stores, and vector databases.
Solid knowledge of MLOps, AI operations, and end-to-end data lifecycle management.
Hands-on experience with AWS, Azure, or GCP AI ecosystems and enterprise integration patterns.
Ability to translate complex business requirements into practical AI, ML, automation, or software solutions.
Experience defining architecture standards, governance frameworks, and technical guidelines.
Strong communication and stakeholder management skills, including whitepaper development and technical presentations.
Experience in NLP, conversational AI, intelligent automation, or related AI domains.
Telecom industry knowledge is an advantage.
Certifications in AI/ML, Cloud, or Architecture frameworks (e.g., TOGAF) are preferred.
