Provide solution architecture and technical design assurance for agentic artificial intelligence solutions across Unilever.
Responsibilities
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 ensure solutions meet agreed architecture and engineering standards before 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.
Design and build agentic solutions and in-product AI assistants for end users, build MCP servers and tool integrations, build retrieval pipelines, integrate LLM providers, work with engineers, document architecture.
Responsibilities
Design and build agentic solutions and in-product AI assistants for end users
Build MCP servers and tool integrations so LLMs can safely work with the product's APIs and data
Build retrieval (RAG) pipelines and manage how much load AI features put on the production database
Integrate LLM providers and manage prompts, structured output, validation, cost and failure handling
Work with the existing engineers on feature development when needed
Requirements
Nice to have: AI assistants in SaaS product
Nice to have: Java front-end experience (React, Vue or Angular)
Nice to have: protecting production database from heavy AI workloads
Machine Learning Associate Advisor role focused on transforming healthcare using AI and ML algorithms, specifically developing LLM, GenAI, and Agentic solutions.
Responsibilities
Embed with Business and Product Development to ship production AI systems
Architect scalable, resilient generative and agentic AI solutions for the business
Build with large language models, open-source models, machine learning
Leverage Large Language Models (LLMs) in the enterprise in a compliant and secure manner
Focus on speed to market and getting Products and Services in the hands of customer
Serve as the technical lead, establishing code standards, architectural best practices, and benchmarks to elevate development excellence across the team.
Partner with sales and tech leadership to define requirements for high‑value opportunities, deploying specialized experts (agentic systems in customer experience) to key accounts.
Lead technical hiring for Applied AI Agent Development, evaluating AI Agent expertise, systems development, and coding skills to build an exceptional development team.
Identify skill gaps in emerging tech (MCP, tool‑calling, and foundation models), ensuring the team maintains subject matter expertise in an evolving AI stack.
Collaborate with product and development to resolve blockers and translate field insights into roadmaps while building internal tools to drive organizational efficiency.
Requirements
Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
Nice to have: Master’s degree or PhD in AI, Computer Science, or related technical fields.
Nice to have: 8 years of experience managing software development, agent development, or similar technical customer‑facing teams in a cloud computing environment.
Nice to have: Experience designing end‑to‑end secure, observable multi‑agent systems using design patterns (ReAct, self‑reflection).
Nice to have: Experience designing intuitive interfaces for AI and agentic systems, prioritizing context development, transparency, and explainability to foster user trust.
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