AI Engineer

📋 Description

• Develop and enhance multi-agent systems and agentic workflows utilizing frameworks like AWS Agent Core and AWS Bedrock Flows (or similar orchestration tools).

• Design and incorporate Retrieval-Augmented Generation (RAG) pipelines for internal applications.

• Create LLM-driven chatbots, assistants, and autonomous agents customized for specific business scenarios.

• Work closely with the Team Lead to grasp requirements and convert them into dependable, scalable implementations.

• Refine existing proof-of-concept or ongoing AI systems to meet production-grade standards.

• Integrate AI components within the AWS and Databricks ecosystems, ensuring reliable end-to-end data and model workflows.

• Implement best practices in observability, logging, and monitoring for deployed AI systems.

• Contribute to CI/CD processes for model and prompt deployment as needed.

• Guide and assist other engineers within the AI domain.

• Clearly communicate progress, challenges, and technical choices to both technical and non-technical stakeholders.

• Engage in technical discussions and contribute to architectural decisions for AI systems.

⛳️ Requirements

• Strong background in data science, data engineering, or a related field, with hands-on AI/ML experience.

• Demonstrated, practical experience in building agentic AI systems, LLM-powered applications, and RAG pipelines—not limited to training classifiers or regressors.

• Proficient understanding of the AWS ecosystem, especially services pertinent to AI/ML workloads (e.g., Agent Core, Bedrock, SageMaker, or AWS Runs).

• Experience with Databricks for data engineering, ML pipelines, or model serving.

• Capability to work autonomously, manage your own deliverables, and produce clean, maintainable code.

• Experience with LLM orchestration frameworks such as LangChain, LlamaIndex, or LangGraph (preferred).

• Familiarity with vector databases or graph-based retrieval methods (preferred).

• Exposure to Slack API integrations or developing knowledge tools on internal communication platforms (preferred).

• Understanding of prompt engineering, LLM evaluation, or fine-tuning processes (preferred).

• Knowledge of MLOps or LLMOps practices, including model versioning and deployment automation (preferred).

• Experience in regulated or compliance-focused environments (preferred).

🏝️ Benefits

• 100% Remote Work

• WFH allowance: Monthly financial support for remote working.

• Career Growth: We have a career development program available for all employees, featuring 360º feedback to assist in your career advancement.

• Training: Employees are allocated time during the week for technical training at Zartis. Options include online courses (from platforms like Pluralsight and Educative.io), English classes, books, conferences, and events.

• Mentoring Program: Opportunities to act as a mentor at Zartis or receive mentorship, or both.

• Zartis Wellbeing Hub (Kara Connect): A platform offering sessions with various specialists, including mental health professionals, nutritionists, physiotherapists, fitness coaches, and webinars with these professionals.

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