AI Engineer creating scalable AI solutions for Rabobank's customer - facing platforms. Collaborating with multidisciplinary teams to improve AI Agent performance for 9.5 million customers.
About the role
- Applied AI Engineer at Parts Town advancing internal AI capabilities by developing ML-based solutions. Collaborating with teams to improve business workflows and operational challenges.
Responsibilities
- Design, develop, and deploy LLM and ML based AI solutions into production
- Build and maintain RAG pipelines, prompt orchestration workflows, and AI-driven automation systems
- Develop scalable inference services, APIs, and integration layers
- Investigate and resolve complex system and data challenges across AI pipelines, diagnosing root causes and implementing robust solutions
- Define and implement evaluation frameworks to assess AI performance, reliability, and business impact
- Integrate AI systems with cloud data platforms and enterprise applications
- Partner with business stakeholders to translate operational challenges into structured, measurable AI solutions
- Contribute to architectural decisions that ensure scalability, maintainability, and clear system boundaries
- Uphold strong engineering standards, documentation practices, and reproducibility across AI systems
Requirements
- Strong problem ‑ solving skills, intellectual curiosity, and a builder mindset to break down ambiguous problems and design, prototype, and iterate on AI or software solutions
- Strong Python skills with solid software engineering fundamentals and experience deploying ML/AI systems into production
- Experience building APIs or service ‑ based architecture and working with LLM ‑ based systems (RAG, prompt orchestration, evaluation frameworks)
- Experience working with cloud platforms and operating effectively in fast ‑ evolving, ambiguous environments with a strong sense of ownership
- Can balance execution speed with engineering discipline and communicate technical concepts clearly to business stakeholders
- Bonus points if: Experience with enterprise data platforms, semantic modeling, ontology ‑ driven or knowledge ‑ based systems
- Bonus points if: Experience integrating AI solutions into operational business workflows
- Bonus points if: Familiar with monitoring, observability, and MLOps practices supporting production AI systems
Benefits
- Quarterly profit-sharing bonus
- Hybrid Work schedule
- Team member appreciation events and recognition programs
- Volunteer opportunities
- Casual dress code
- On demand pay options: Access your pay as you earn it, to cover unexpected or even everyday expenses
- All the traditional benefits like health insurance, 401k/401k match, employee assistance programs and time away
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