Brainbox Consulting BV aligning great talent with clients’ needs is at the core of who we are. We are passionate about our consultants, our clients, and our Partners. Our rich IT legacy combined with our unyielding care for our people and business is the driving force behind all we do, and we deliver! On this journey, we are looking for Agentic AI Engineer – Generative & Agentic AI who is also interested to take on a wide range of activities.
Description:
Transform Generative AI and Agentic AI prototypes into scalable, production-ready solutions for real-world engineering workflows. This role involves working closely with AI Solution Architects and engineering teams to make data AI-ready, integrate AI capabilities across systems and workflows, and embed intelligent solutions into daily engineering processes. Hands-on experience across low-code and pro-code environments with technologies such as Azure AI Foundry, AWS Bedrock, Microsoft Copilot Studio, ChatGPT/Codex, and Anthropic Cowork is highly relevant, with a strong focus on AI solution integration, productization, scalability, and adoption.
Responsibilities:
- Prepare, structure, curate, and organize AI-ready data for Generative AI and Agentic AI applications.
- Identify and resolve data quality issues and gaps across databases, knowledge bases, and other data sources.
- Design and implement data and system integrations using APIs and MCP (Model Context Protocol).
- Connect AI solutions with enterprise systems, engineering tools, and knowledge sources.
- Collaborate directly with engineering teams to implement, integrate, and adopt AI solutions.
- Support development across low-code and pro-code AI environments.
- Transform AI prototypes and MVPs into reliable, scalable, maintainable, and production-ready solutions.
- Build reusable AI components and integration patterns that can scale across teams and use cases.
- Partner with the AI Solution Architect on technology stack, deployment models, LLM selection, and technical standards.
- Apply AgentOps practices for monitoring, evaluation, observability, feedback loops, and continuous improvement.
- Optimize AI solutions for performance, robustness, scalability, and cost efficiency.
- Ensure AI implementations comply with security, privacy, Responsible AI, governance, and engineering standards.
- Contribute to best practices, reusable playbooks, and implementation standards.
- Use Python and other programming skills to build integrations, services, automation, and AI-enabled applications.
- Take ownership of solutions from prototype → implementation → production → adoption.
Preferred Experience
Experience with:
- 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