In this role, you will work closely with engineering teams to make their data AI-ready, enable integration across systems and workflows, and productize AI solutions developed together with the AI Solution Architect. You act as a hands-on enabler and technical partner, supporting teams in moving from prototype to robust, scalable, and production-ready solutions.
You will work across both low-code and pro-code environments, leveraging tools such as Microsoft Copilot Studio, ChatGPT Codex, Anthropic Cowork, Azure AI Foundry, and AWS Bedrock, ensuring AI capabilities are effectively embedded into engineering workflows. The role operates in a federated model, collaborating with AI Champions and closely partnering with the AI Solution Architect.
Key Responsibilities
1. Data Readiness & AI Foundations
- Support teams in making their data AI-ready, ensuring it is:
- Well curated and structured
- Available in the right format
- Organized in appropriate storage solutions (e.g., databases, knowledge bases)
- Identify and resolve data gaps and quality issues
- Enable data to be effectively used for Generative and Agentic AI applications
2. Data Integration & System Enablement
- Design and implement data integrations via APIs and MCPs (Model Context Protocols)
- Connect AI solutions to enterprise systems, engineering tools, and knowledge sources
- Ensure reliable and scalable data access across workflows
3. Co-Creation & Enablement with Engineering Teams
- Work side-by-side with teams to implement and adopt AI solutions in practice
- Support teams in using both low-code and pro-code AI approaches
- Help teams move from prototype working solution daily usage
4. Productization & Scaling
- Convert MVPs and prototypes into production-ready, reusable solutions
- Ensure solutions are: Reliable and maintainable
- Scalable across teams and use cases
- Integrated into engineering workflows
- Package solutions for reuse across IEN
5. Implementation Alignment & Technical Choices
- Collaborate closely with the AI Solution Architect to:
- Align on technology stack, deployment models, and LLM choices
- Ensure consistency and reusability across solutions
- Contribute to implementation best practices and standards
6. Operational Excellence (AgentOps)
- Apply AgentOps practices for monitoring and continuous improvement
- Optimize solutions for:
- Performance and robustness
- Cost efficiency
- Implement evaluation, feedback loops, and observability
7. Responsible AI & Engineering Standards
- Ensure AI solutions comply with security, privacy, and responsible AI principles
- Align implementations with enterprise standards and governance
- Contribute to reusable components, integration patterns, and playbooks
Functie-eisen
- Strong experience in building AI-enabled applications, integrations, or data-driven systems
- Solid programming experience (including Python) for building integrations, services, or automation
- Structure and prepare data for AI use cases
- Integrate systems via APIs
- Experience taking solutions from prototype to production
- Strong collaboration skills, working directly with engineering teams
Preferred Experience
- Data engineering, APIs, and system integration in complex environments
- Generative or Agentic AI solutions in production settings
- AgentOps, monitoring, and optimization practices
- Experience in engineering-heavy environments (software, systems, manufacturing)
- Experience working across both low-code and pro-code environments:
- Low-code / no-code AI tools:
- Microsoft Copilot Studio
- ChatGPT Codex
- Anthropic Cowork
- Pro-code / platform-based AI development:
- Azure AI Foundry
- AWS Bedrock or similar platforms
- Familiarity with enterprise AI governance frameworks
- Experience working in federated or transformation programs
Competenties
- Engineering teams have AI-ready data foundations enabling reliable AI use cases
- AI solutions are integrated into systems and workflows, not isolated tools
- MVPs are successfully productized into scalable, reusable solutions
- APIs and MCPs enable seamless integration across workflows
- Solutions operate with strong performance, reliability, and cost efficiency
- Reusable components and patterns accelerate AI adoption across IEN
Bedrijfsinformatie
Join Philips Innovation Engineering as an Agentic AI Engineer and help teams operationalize Generative and Agentic AI in real engineering workflows. You work hands-on to make data AI-ready, integrate systems, and transform prototypes into robust solutions embedded in daily work.
Working closely with AI Solution Architects and engineering teams, youll ensure AI solutions are not just built-but scaled, integrated, and adopted.
Inclusiviteit en diversiteit
Uiteraard staat deze vacature open voor iedereen die zich hierin herkent. We geloven dat diverse teams van belang zijn voor ons als lerende organisatie, die voorop wil blijven lopen in de wereld van werk. Want juist verschillen tussen mensen zorgen voor groei. Van collega's, klanten, kandidaten en daarmee van Randstad Professional. Heb jij een uniek talent? We ontmoeten je graag.