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Avaron

Senior HR AI Solution Architect

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.

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