AI Engineer

We are:
Wizeline a global AI-native technology solutions provider develops cutting-edge AI-powered digital products and platforms. We partner with clients to leverage data and AI accelerating market entry and driving business transformation. As a global community of innovators we foster a culture of growth collaboration and impact.

With the right people and the right ideas theres no limit to what we can achieve.

Are you a fit
Sounds awesome right Now lets make sure youre a good fit for the role:

• Architect and ship end-to-end agentic and LLM-powered tools for business-facing use cases deciding when to use a single LLM call an iterative LLM loop or a full multi-agent system based on real task complexity.
• Design AI-agnostic model-flexible services that allow the team to evaluate and swap the best-performing model for each task.
• Build production tools that transform raw content into structured ready-to-use output for example systems that reformat content to defined templates/guidelines or consolidate multiple sources into a single fact-accurate output without inventing information.
• Develop and maintain RAG pipelines and vector database integrations to support retrieval-driven features such as content linking and recommendations.
• Establish and scale prompt evaluation testing and regression-control frameworks (e.g. via Braintrust MCP tooling LangFuse) so quality holds as tools expand across teams and use cases.
• Take AI features from prototype/PoC through to deployed end-user-facing production tools working across the full stack (AI core services in Python/TypeScript front-end integration in React/Vue/) without relying on handoffs to other teams.
• Partner with stakeholders and engineering leadership to gather feedback measure impact (e.g. time saved approval rates) and iterate on tools in production.
• Extend proven architectures to onboard new use cases as configuration rather than one-off rebuilds.
• Stay current on GenAI NLP ML and IR technologies incorporating best practices and cloud infrastructure to improve system efficiency.

• Bachelors or Masters degree in Computer Science Engineering Data Science or a related STEM field or equivalent work experience.
• 4 years of industry experience in machine learning engineering AI engineering or a related software engineering role.
• Strong programming skills in Python and/or TypeScript/ with the ability to build both AI core services and the interfaces that consume them.
• Hands-on experience deploying LLMs in production building automated evaluation pipelines (e.g. LLM-as-a-judge) and architecting multi-agent systems that use tool-calling and long-term memory to solve non-linear problems.
• Practical experience with LangChain and its ecosystem (e.g. LangGraph LangSmith) or comparable agent-orchestration frameworks.
• Experience with RAG architectures and vector databases in production settings.
• Full-stack capability (front-end frameworks such as React/Vue plus back-end services on cloud infrastructure such as AWS/GCP) sufficient to ship complete features independently.

• Experience with Vertex AI or equivalent multi-model cloud AI platforms.
• Familiarity with prompt-management and observability tooling such as Braintrust LangFuse or MCP-based systems.
• AI Tooling Proficiency: comfort using AI tools to optimize day-to-day work (drafting analysis research automation) with the ability to recommend effective AI use and identify workflow improvements for the team.
• Familiarity with Docker and Git version control.
• Experience consuming and integrating third-party APIs reliably and securely.

• A High-Impact Environment
• Commitment to Professional Development
• Flexible and Collaborative Culture
• Global Opportunities
• Vibrant Community
• Total Rewards

Specific benefits are determined by employment type and location.

Find out more about our culture here.