# Solution Architect - Agent Catalogue at Unilever

Unilever is hiring a Solution Architect - Agent Catalogue. Level rates it Works on AI ●●●○; you can [apply on Unilever](https://jobsbylevel.com/go/a05788ac-30a1-44e7-a8fa-aa6d40925c5d?utm_medium=ai-agent).

AI Level 3, AI centrality 74 out of 100. Uniops Bangalore Centre.

## Details

- Company: [Unilever](https://jobsbylevel.com/companies/unilever)
- AI level: AI Level 3 (score 74 out of 100)
- Location: Uniops Bangalore Centre
- Posted: November 11, 2026
- Apply: https://jobsbylevel.com/go/a05788ac-30a1-44e7-a8fa-aa6d40925c5d?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=solution-architect-agent-catalogue-at-unilever-68fca1

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## Description

Job Title: Solution Architect - Agent Catalogue Work Level: 2A JOB PURPOSE We are looking for a Manager, Agentic Solution Architecture & Reuse to provide hands-on solution architecture and technical design assurance for agentic artificial intelligence solutions across Unilever. As agentic artificial intelligence adoption continues to scale across technologies and business domains, you will make sure our agentic solutions are secure, scalable, cost-efficient, reusable and future-fit. You will work across technology platforms rather than being tied to a single vendor stack, ensuring the right architecture, models, integration patterns, skills and governance controls are applied consistently as solutions move from experimentation into production and scale. You will also anchor two critical enterprise capabilities: token and model optimisation, continuously improving the efficiency and cost of agentic workloads; and Agent Catalogue and Skill Registry hydration, making sure proven agents, skills and architecture patterns are captured, governed and reused across Unilever rather than repeatedly rebuilt. You will work closely with product teams, engineers, platform teams, security, Enterprise Architecture and business stakeholders as part of the Hyper Automation Technical Design Authority. Because here, we don’t just hire for jobs. We invite you to be part of something bigger. KEY RESPONSIBILITIES undefined Provide solution architecture for artificial intelligence and agentic use cases across multiple technologies and platforms. Translate business requirements into robust technical architectures covering agents, models, skills and tools, data, integration and orchestration. Conduct technical design reviews and make sure solutions meet agreed architecture and engineering standards before progressing to build and production. Determine when requirements should be met through native platform capabilities, reusable enterprise capabilities or custom pro-code development, keeping architectures portable and avoiding unnecessary platform lock-in. Define and apply architecture patterns covering orchestration, grounding, agent-to-agent interaction, human-in-the-loop, application programming interfaces, Model Context Protocol (MCP) and tool integration, and deterministic automation. undefined Make sure agentic solutions are designed for enterprise scale rather than individual proofs of concept or isolated use cases. Assess designs for scalability, resilience, observability, maintainability, security and cost. Monitor the evolution of models, agent frameworks and platform capabilities, and determine where existing architecture patterns need to evolve. Partner with the Senior Manager, AI Solution Architecture and Enterprise Architecture to convert emerging approaches into approved reusable patterns. Support the progression of solutions towards greater autonomy while maintaining appropriate control, audit and human intervention points. undefined Embed security, privacy, Responsible AI and governance requirements directly into solution design. Make sure agent identity, permissions, data access, tool access and execution boundaries are appropriately designed. Maintain traceability of architecture decisions and exceptions, identify architectural risks early and drive remediation before production deployment. Make sure reusable assets have clear technical ownership and lifecycle accountability. undefined Anchor token optimisation across agentic workloads, analysing excessive context, prompts, agent interactions and model calls and recommending architectural optimisation. Drive patterns such as context reduction, better retrieval, reusable system instructions, efficient agent and tool interaction and right-sized model selection. Work with solution teams to improve cost per outcome, not simply model cost per token, and identify where smaller, lower-cost models can safely replace larger models for defined task classes. Build innovative solutions that

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