AI Engineer EMEA LATAM

About the role

We’re looking for an AI Engineer to help us build and scale the next generation of AI-powered systems at Starbridge . You’ll work on projects that sit at the core of our product—building, evaluating, and deploying LLM-driven features that make it easier for organizations to access, understand, and act on complex public data.

You’ll collaborate closely with our engineering and product teams to design new AI capabilities, such as deep document analysis and interactive chat experiences. This role combines hands-on software engineering, applied machine learning, and product experimentation, with the goal of delivering reliable, high-performing AI systems to production.

You’ll have the opportunity to work with models from OpenAI, Anthropic, and Gemini , contribute to our AI infrastructure, and play a key role in shaping how we leverage generative AI across our platform.

Your responsibilities

Collaborate closely with our team as we productize new AI-powered capabilities: such as AI proposal writing & search experiences.

Evaluate and monitor the performance of AI models (we will work with models from OpenAI, Anthropic, Gemini, Parallel.ai) & systems through rigorous testing and experimentation.

Stay up-to-date with the latest advancements in AI and machine learning research, and proactively suggest improvements to enhance our generative AI capabilities.

Implement strong testing and CI/CD practices that help us move with confidence in our AI system development

Is this you?

Bachelor’s degree in Computer Science, Engineering, Mathematics, related field, or equivalent experience

Have experience working in a startup or a smaller company with real engineering impact.

5+ years of professional experience in software engineering, AI/ML development including:

Proficiency with production software (Python) and systems design

Machine learning algorithms and model development techniques

ML lifecycle tools like MLflow, dvc, weights & biases

Cloud deployment of ML systems

Professional experience with LLMs and large-scale models

Very strong software engineering skills with a track record of building scalable, distributed product machine learning systems

Product thinking: ability to take product requirements and strategize how to apply LLMs

Ability to communicate complex ideas and concepts effectively

Preferred Skills:

Experience building scalable applications with LLMs, using frameworks such as LangGraph, LiteLLM, Agent Client Protocol, and Koog

Depth of knowledge with RAG implementation and improvements

Proficiency with Kotlin

Interview Process

We move fast — really fast. Getting back to someone today beats tomorrow, and our interview process reflects that mindset. Please keep us p