De positie
Build the next generation of AI-enabled engineering workflows in wireless connectivity
Within Philips IP&S, we are shaping how Generative AI transforms complex, knowledge-intensive engineering domains.
We are looking for a Generative AI Architect to help design and build AI-powered workflows for our Wireless Connectivity Standardization team, working across 5G, 6G, Wi-Fi, and future connectivity standards.
This role sits at the intersection of Generative AI, knowledge systems, and advanced engineering workflows, where the goal is not experimentation; but real adoption in high-impact technical processes.
Context
Wireless standardization and intellectual property workflows are highly structured, fast-moving, and information-dense environments.
Teams continuously work with:
- Technical specifications and standardization documents
- Intellectual property and patent-related content
- Cross-functional engineering inputs across global ecosystems
- Large volumes of structured and unstructured technical knowledge
The opportunity is to fundamentally improve how this knowledge is created, processed, analyzed, and reused using Generative AI.
The Role: AI applied to high-stakes engineering workflows
You will design and implement GenAI-driven systems that enhance how experts work, rather than replacing them.
This includes building systems that:
- Accelerate understanding of complex technical documentation
- Improve consistency and quality of structured outputs
- Support IP and standardization workflows with AI-assisted automation
- Enable knowledge retrieval and reuse across large document ecosystems
A core principle in this role is human-in-the-loop AI design, where domain experts remain in control, and AI acts as an intelligent augmentation layer.
Over het bedrijf
With a growing presence in cardiology, oncology, and women's health, Philips operates in the areas of Imaging Systems, Patient Care & Clinical Informatics, Home Healthcare and Customer Services. Philips combines its clinical expertise and human insights to create innovative solutions across the continuum of care, in partnership with clinicians and our customers, to provide better value and expand access to care for millions. Our teams are working hard every day to improve patient outcomes all the way from disease prevention and screening to diagnosis, treatment, therapy monitoring, and disease management. Irrespective of whether the care cycle takes the patient from doctor's office to hospital or hospital to home, or simply from one medical department to another, Philips Healthcare's unique medical solutions are designed to optimize the quality and flow of patient information and clinical decision making.
Wat breng jij
What you will do
You will work closely with wireless connectivity experts and engineering stakeholders to translate high-value use cases into scalable AI solutions.
Key responsibilities include:
- Design and build scalable Generative AI solutions using LLMs, RAG architectures, and agent-based systems
- Improve and extend existing AI copilots and internal AI assistants
- Develop workflow automation for IP lifecycle and standardization processes, including:
- structured summarization of technical content
- metadata generation and enrichment
- workflow updates and knowledge tracking
- Prototype advanced AI capabilities such as:
- intelligent document retrieval across large technical corpora
- topic identification and semantic clustering
- AI-assisted document improvement and refinement
- Define and implement evaluation frameworks to ensure reliability, robustness, and accuracy of AI outputs
- Build reusable components, libraries, and architectural patterns for long-term scalability
- Partner closely with domain experts who define technical logic and requirements, while you lead AI architecture, tooling, and implementation environments
Required experience & capabilities
We are looking for someone who operates comfortably at the intersection of AI engineering and applied system design.
- Strong experience with Generative AI systems in production or near-production environments
- Hands-on expertise in:
- LLM-based application design
- Retrieval-Augmented Generation (RAG) systems
- Agentic AI / orchestration frameworks
- Prompt and context engineering at system level
- AI evaluation methodologies and quality frameworks
- Experience with data pipelines and integration of AI systems into enterprise environments
- Proven ability to move from prototype → reliable internal product → scalable system
- Strong collaboration skills in multidisciplinary technical environments
- Ability to work closely with domain experts and translate expert knowledge into AI system design
- Experience in telecom, wireless systems, semiconductor, or standardization environments is highly valued
What makes this role unique
This is not a typical AI prototyping role.
You will be working in a space where:
- AI directly impacts engineering output quality and speed
- Knowledge systems are mission-critical and highly specialized
- Reliability and correctness matter as much as innovation
- AI is embedded into structured technical workflows, not standalone tools
You will help define how Generative AI becomes a repeatable capability inside engineering-driven organizations, rather than isolated experimentation.
Why this role exists
Generative AI is rapidly changing how technical organizations work—but most implementations remain fragmented or experimental.
This role exists to bridge that gap by building:
- production-grade AI workflows
- reusable AI capabilities across teams
- scalable knowledge systems for wireless engineering domains
The goal is to move from AI experimentation → operational AI capability embedded in engineering workflows.
Impact you will have
You will directly contribute to:
- Faster and higher-quality wireless standardization processes
- Improved consistency and reuse of technical knowledge
- Reduced manual effort in IP and documentation workflows
- Scalable GenAI capabilities that extend beyond a single team or use case
