AI Engineer

European UnionAI Consultantmid

Machine Learning EngineerData

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Quick Summary

Overview

AI Engineer The company and our mission: Zartis is a global AI transformation and technology consulting partner where talented engineers and technologists work on cutting edge innovation.

Key Responsibilities

Build and extend multi-agent systems and agentic workflows using frameworks such as AWS Agent Core and AWS Bedrock Flows (or equivalent orchestration tools). Develop and integrate Retrieval-Augmented Generation (RAG) pipelines for internal tools.

Requirements Summary

Experience with LLM orchestration frameworks such as LangChain, LlamaIndex, or LangGraph. Familiarity with vector databases or graph-based retrieval techniques.

Technical Tools

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Zartis is a global AI transformation and technology consulting partner where talented engineers and technologists work on cutting edge innovation. We partner with ambitious organizations to design, build, and scale technology solutions that deliver real impact.

Our teams bring deep expertise in AI driven platforms, secure API architectures, and cloud native engineering. You will work on meaningful projects that accelerate the adoption of advanced technologies, from strategy and discovery through to full product delivery, helping turn complex challenges into measurable outcomes.

With engineering hubs across EMEA and LATAM, and long term partnerships in financial services, healthcare and life sciences, and energy and climate, we offer opportunities to work on projects that truly matter. Here, you will not just build technology, you will drive business impact and grow your career alongside industry leaders.

We are looking for an AI Engineer to work on a project in the green energy industry.

Our teammates are talented people that come from a variety of backgrounds. We’re committed to building an inclusive culture based on trust and innovation.

You will be part of a distributed AI & Data team undergoing a large-scale AI transformation, working alongside a Head of Data Science and experienced engineers to build cutting-edge agentic and generative AI solutions.

We are looking for someone with a data science or data engineering background, a hands-on attitude, and a track record of delivering AI systems in real-world environments.

Responsibilities

~1 min read

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Build and extend multi-agent systems and agentic workflows using frameworks such as AWS Agent Core and AWS Bedrock Flows (or equivalent orchestration tools).
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Develop and integrate Retrieval-Augmented Generation (RAG) pipelines for internal tools.
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Implement LLM-powered chatbots, assistants, and autonomous agents tailored to specific business use cases.
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Collaborate closely with the Team Lead to understand requirements and translate them into reliable, scalable implementations.
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Take existing proof-of-concept or in-progress AI systems and harden them to production-grade standards.
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Pipeline AI components together within the AWS and Databricks ecosystem, ensuring reliable end-to-end data and model workflows.
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Apply best practices in observability, logging, and monitoring for deployed AI systems.
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Contribute to CI/CD processes for model and prompt deployment where applicable.
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Mentor and support other engineers within AI.
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Communicate progress, blockers, and technical decisions clearly to both technical and non-technical stakeholders.
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Participate in technical discussions and contribute to architectural decisions for AI systems.

Responsibilities

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Solid background in data science, data engineering, or a related discipline, with practical AI/ML experience.
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Proven, hands-on experience building agentic AI systems, LLM-powered applications, and RAG pipelines — not just training classifiers or regressors.
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Strong working knowledge of the AWS ecosystem, particularly services relevant to AI/ML workloads (e.g. Agent Core, Bedrock, SageMaker, or AWS Runs).
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Experience with Databricks for data engineering, ML pipelines, or model serving.
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Ability to work independently, manage your own delivery, and produce clean, maintainable code.

Nice to Have

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Experience with LLM orchestration frameworks such as LangChain, LlamaIndex, or LangGraph.
Familiarity with vector databases or graph-based retrieval techniques.
Exposure to Slack API integrations or building knowledge tools on top of internal communication platforms.
Understanding of prompt engineering, LLM evaluation, or fine-tuning workflows.
Knowledge of MLOps or LLMOps practices, including model versioning and deployment automation.
Experience working in regulated or compliance-aware environments.

What We Offer

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WFH allowance: Monthly payment as financial support for remote working.

Career Growth: We have established a career development program accessible for all employees with a 360º feedback that will help us to guide you in your career progression.

Training: For Tech training at Zartis, you have time allocated during the week at your disposal. You can request from a variety of options, such as online courses (from Pluralsight and Educative.io, for example), English classes, books, conferences, and events.

Mentoring Program: You can become a mentor in Zartis or you can receive mentorship, or both.

Zartis Wellbeing Hub (Kara Connect): A platform that provides sessions with a range of specialists, including mental health professionals, nutritionists, physiotherapists, fitness coaches, and webinars with such professionals as well.

Multicultural working environment: We organize tech events, webinars, parties, and activities to do online team-building games and contests.