About this Opportunity :

We are seeking a seasoned AI & Data 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 robust 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:

- Data modelling (conceptual/logical)

- Data pipelines (ETL/ELT) and data engineering practices

- Data 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.

📌 Technical Architect, AI and Data (Noida)
🏢 Ericsson
📍 Noida