About the Company

Avaron AB is a growing consultancy focused on technology, finance, and business support. We match your expertise with the market's most interesting assignments, offering a platform where your professional development is central.

About the Assignment

In this assignment you will help a global organization modernize HR through AI—combining human insight with intelligent, autonomous systems to create faster, fairer, and more seamless employee experiences. You will take a leading role in shaping architecture, standards, and ways of working so HR teams can experiment responsibly and scale what works across the enterprise.

You will operate in a hybrid technology environment with strong collaboration across HR stakeholders, product teams, engineering, security, data, and compliance.

Job Description

• Lead solution architecture for AI components across HR processes such as talent acquisition, employee services, and workforce planning.
• Design and enable multiple AI paradigms, including Generative AI, agentic AI, and information extraction.
• Select fit-for-purpose architectural patterns and toolchains within the enterprise ecosystem.
• Define reference architectures and non-functional guardrails for performance, reliability, observability, and cost.
• Design end-to-end agent execution with controlled latency and token usage, including retries, error handling, and graceful degradation.
• Ensure solutions run effectively across hybrid environments.
• Coach HR product teams, engineers, and analysts in AI design, experiment backlogs, and quality practices.
• Create reusable starter kits, templates, and “golden paths” to accelerate delivery.
• Embed pragmatic AI and data governance aligned with frameworks such as NIST AI RMF, ISO/IEC 42001, and the EU AI Act.
• Partner with security, data, and compliance to deliver safe and explainable outcomes.
• Support product operating models with clear roles, SLAs, rollout steps, and measurement for continuous improvement.
• Define how agentic systems are measured over time (value, cost, reliability, and human oversight).

Requirements

• Senior-level enterprise architecture experience, including designing scalable, production-grade solutions and establishing reference designs and standards.
• Hands-on experience architecting and designing production-grade GenAI and agentic systems (e.g., ReAct, tool use, multi-agent orchestration, retrieval-augmented generation).
• Experience with managed and/or self-hosted LLM platforms (e.g., Azure OpenAI or equivalent), including model selection, prompt lifecycle management, versioning, and rollback strategies.
• Practical experience with agent frameworks/orchestration layers (e.g., Semantic Kernel, AutoGen, MS Agent Framework, or custom implementations), including tool-calling, state management, and multi-agent coordination.
• Experience designing RAG systems beyond basics, including chunking strategies, embedding lifecycle, relevance tuning, access control, and data drift handling.
• Ability to define evaluation criteria and test cases for agents, including hallucination/failure detection, human-in-the-loop thresholds, and safe fallback/kill-switch mechanisms.
• Experience designing for token efficiency and latency control, including caching/batching and observability of agent behavior in production.
• Familiarity with responsible AI governance and risk controls, balancing innovation with safety and trust (e.g., NIST AI RMF, ISO/IEC 42001, EU AI Act).
• Strong enablement capability: coaching teams and aligning stakeholders to deliver outcomes.
• Experience working with Azure and the Microsoft ecosystem in modern AI stacks.

Nice to have

• Experience integrating HR systems (HCM, case management) with AI services.
• Familiarity with recruitment marketing and alignment with Employee Value Proposition.

Application

Selections are made on an ongoing basis, so we recommend that you apply as soon as possible.