Role: IT & Information Security - Other
Industry Type: Miscellaneous
Department: IT & Information Security
Employment Type: Full Time, Permanent
Role Category: IT & Information Security - Other
UG: B.Tech / B.E. in Any Specialization
PG: M.Tech in Any Specialization, MCA in Any Specialization
Job Title: Technical Architect, AI and Data We are seeking a seasoned AI Architect to join the Architecture & Technology Board, driving AI architecture direction and adoption across Service Delivery. This role ensures fit-for-purpose, scalable, and responsible AI usage aligned with enterprise goals, while enabling development teams to build consistent, reusable, and production-ready AI applications through strong governance and best practices.
Responsibilities
1. AI Governance & Architecture Oversight Define and govern AI/ML, GenAI, and data architecture standards, patterns, and guardrails Review and approve AI-related solutions within the Architecture & Technology Forum Ensure alignment with enterprise architecture, data governance, security, and compliance Provide governance and guidance on AI platform capabilities including Model Context Protocol (MCP), Agent-to-Agent (A2A) communication, AI Gateways, and observability frameworks, ensuring secure, scalable, and well-orchestrated AI systems Provide oversight on production-grade AI deployments, ensuring scalability, reliability, and observability Ensure strong data lifecycle management including data quality, lineage, governance, and compliance Establish and maintain baseline architecture for existing AI services and data ecosystems 2. Use Case Assessment & Fitment Evaluate business use cases for AI applicability, feasibility, and value realization Guide teams in selecting the right approach (AI vs automation vs traditional solutions) Ensure optimal technology fitment, avoiding overuse or misuse of AI 3. Enablement & Best Practices Define and promote best practices for AI application design, data pipelines, and lifecycle management Guide engineering teams on architecture patterns, integration approaches, and data flows Enable reuse of AI components, datasets, and standardized solution patterns 5. Technology Leadership & Innovation Stay current with latest advancements in AI/ML, GenAI, and enterprise AI platforms Evaluate emerging technologies and define adoption strategy for Service Delivery Publish whitepapers, architectural guidelines, and thought leadership on AI in Service Delivery 6. Collaboration & Reuse Across Ericsson Collaborate with other Ericsson organizations, architecture teams, and innovation units to understand ongoing AI initiatives Leverage and integrate existing platforms, solutions, and learnings, avoiding duplication of efforts Drive reuse, standardization, and alignment across units for consistent AI adoption Act as a bridge between global initiatives and Service Delivery implementation
Required Skills
and Qualifications: Strong experience in AI/ML architecture with prior hands-on exposure to AI application development Proven experience in governing or leading production-grade AI/ML deployments Expertise in GenAI, LLMs, RAG architectures, and enterprise AI solution patterns Solid understanding of data architecture fundamentals: áData modelling (conceptual/logical) áData pipelines (ETL/ELT) and data engineering practices áData quality, lineage, and governance Experience with data platforms (data lakes, warehouses, streaming systems) Knowledge of feature stores, vector databases, and data foundations for AI/GenAI Strong understanding of AI lifecycle management (MLOps) and data lifecycle management Experience with cloud AI ecosystems (AWS, Azure, GCP) and integration patterns Ability to assess business use cases and map them to appropriate AI/automation solutions Experience defining architecture standards, guidelines, and governance frameworks Strong communication and thought leadership capabilities (whitepapers, forums, strategy articulation) Good to have: Experience in NLP, conversational AI, or automation in Service Delivery contexts. Certifications in AI/ML, Cloud, or Architecture frameworks (TOGAF, etc.), Telecom Domain Knowledge.