Job Title: Solution Architect - Skills & Reusability

Work Level: 2B

JOB PURPOSE

We are looking for a Senior Manager, AI Solution Architecture to provide end-to-end architecture leadership for enterprise artificial intelligence and agentic solutions across technologies and platforms.

As part of the Hyper Automation Technical Design Authority, you will make sure solutions are secure, scalable, reusable, cost-efficient and future-fit. You will be accountable for agentic architecture, grounding and retrieval, integration patterns, model selection and benchmarking, evaluation, large language model operations, model drift and token and cost optimisation.

This is a technical design authority role rather than a delivery engineering role: you will decide and assure the architecture while partnering with the product and engineering teams that build, deploy and operate solutions.

You will work closely with Enterprise Architecture, security, privacy, engineering and platform teams, and with technology vendors, to turn emerging artificial intelligence capabilities into practical enterprise patterns.

Because here, we don’t just hire for jobs. We invite you to be part of something bigger.

KEY RESPONSIBILITIES

• Define and govern reference architectures and engineering patterns for artificial intelligence, generative artificial intelligence and agentic solutions.
• Lead technical design reviews and provide clear design pass, hold or remediation decisions.
• Design enterprise patterns for agent orchestration, retrieval and grounding, application programming interfaces, tools, skills and enterprise-system integration.
• Assess artificial intelligence models for task suitability, quality, latency, security, economics and operational fit, and establish benchmarking approaches across model and workload classes.
• Drive token optimisation and cost-per-outcome engineering, including appropriate use of smaller, lower-cost models and routing strategies.
• Define evaluation, observability, large language model operations (LLMOps) and model-drift patterns, including criteria to hold, roll back or promote solutions.
• Determine when model tuning is justified versus prompting, retrieval, tool and skill design or model selection.
• Build proofs of value for emerging technologies and convert successful findings into reusable enterprise patterns.
• Identify opportunities for reuse before new engineering is commissioned.
• Work across platform boundaries, including cloud artificial intelligence platforms, agent frameworks and deterministic automation technologies.
• Partner with Enterprise Architecture, security, privacy and engineering teams to make sure designs meet enterprise guardrails.
• Help mature solutions along the autonomy ladder, introducing appropriate human-in-the-loop, self-monitoring and automated remediation patterns.

REQUIRED QUALIFICATIONS

• Strong enterprise or solution architecture experience, with hands-on depth in generative and agentic artificial intelligence architecture.
• Proven experience designing production-grade agentic systems, including orchestration, tool and skill invocation, multi-agent patterns and human-in-the-loop controls.
• Strong grounding in large language models and model architecture, including model selection, benchmarking, context and token management and cost optimisation.
• Deep understanding of retrieval-augmented generation, enterprise search, embeddings, vector retrieval, grounding and knowledge integration.
• Strong knowledge of agent integration patterns, including application programming interfaces, event-driven integration and Model Context Protocol (MCP) style tool integration.
• Experience designing evaluation frameworks covering quality, groundedness, task completion, latency, safety and cost.
• Experience with large language model operations (LLMOps) or generative artificial intelligence operations, observability, model drift and production monitoring.
• Strong cloud architecture experience with at least one major hyperscaler, such as Microsoft Azure or Google Cloud Platform.
• Ability to evaluate native platform capability versus custom pro-code engineering based on business value and architectural fit.
• Strong security and Responsible AI architecture understanding, including identity, access control, data boundaries, auditability and guardrails.
• Ability to produce clear technical design documents, reference architectures, architecture decision records and engineering standards.
• Hands-on experience with enterprise artificial intelligence ecosystems such as Microsoft Azure AI, Azure OpenAI and Microsoft Foundry; Google Cloud Vertex AI and Gemini; Anthropic Claude; and Microsoft Copilot Studio and adjacent enterprise agent platforms.
• Experience with agent orchestration frameworks such as Agent Development Kit (ADK), Semantic Kernel or equivalent.
• Strong stakeholder management, with the ability to challenge engineering teams and platform vendors constructively.

PREFERRED QUALIFICATIONS

• Experience with robotic process automation (RPA) and broader hyperautomation architecture.
• Experience with prompt and context engineering.
• Knowledge of artificial intelligence financial operations (FinOps) and model economics.
• Experience with automated testing for artificial intelligence systems and continuous integration and continuous delivery patterns for prompts, agents and evaluations.
• Experience designing self-healing or NoOps-oriented automation patterns.
• Exposure to agent and skill catalogues, reusable components and platform engineering.
• Ability to translate emerging technology into practical enterprise adoption decisions: adopt, wait or stop.
• Experience in fast-moving consumer goods, retail and eCommerce, or global manufacturing organisations, with an understanding of complex global operations, high transaction volumes and supply chain processes.

At Unilever, inclusion is at the heart of everything we do. We welcome applicants from all walks of life and are committed to creating an environment where everyone can thrive/succeed. All applicants will receive fair and respectful consideration, and we actively support the growth and development of every employee.

Unilever is an Equal Opportunity Employer/Protected Veterans/Persons with Disabilities.

ADDITIONAL INFORMATION

This is an opportunity to lead the technical design authority for enterprise artificial intelligence and agentic solutions at global scale.

You will have the opportunity to:

·       Set the reference architectures, standards and design decisions that shape how artificial intelligence is built across Unilever.

·       Lead model selection, benchmarking and evaluation across leading cloud and model providers.

·       Turn emerging artificial intelligence technologies into proven, reusable enterprise patterns.

·       Safely progress solutions towards higher levels of autonomy.

Success in this role will be reflected in:

·       A higher first-time architecture review pass rate.

·       An increased proportion of workloads using right-sized models, and reduced token and model cost per business outcome.

·       Strong model benchmark and evaluation coverage.

·       Increased reuse of approved architecture patterns, with fewer architecture exceptions and less duplicate engineering.