AI Engineer
ANVA’s new, multi-tenant, cloud-native SaaS platform, ANVA 6, forms the foundation for data-driven and AI-powered insurance processes. As an AI Engineer, you’ll play a key role in designing, building, and deploying AI solutions that directly contribute to our products and internal processes. You will take ownership of the entire end-to-end lifecycle of AI components. You will work within an internal AI team and report to the Engineering Manager.
Your impact
With your expertise, you’ll help make AI at ANVA reliable, scalable, and practical. You’ll ensure that AI solutions go beyond the experimental stage and actually deliver value in production. You’ll contribute to a mature AI ecosystem centered on quality, monitoring, and continuous improvement.
This is what you will do
- Designing, prototyping, and developing machine learning and generative AI solutions.
- Building and maintaining model pipelines (feature engineering, training, evaluation, and version control).
- Designing and improving prompts, embeddings, and LLM-based integrations.
- Integrating AI components into backend services and user-facing features.
- Establishing testing, validation, and monitoring procedures for model quality, data drift, and performance.
- Deploying and managing AI solutions using cloud-native tools and CI/CD pipelines.
- Collaborate within an internal cross-functional team with software engineers and Product Owners to clearly define and implement AI features. You will also work closely with colleagues from platform, domain, and data teams.
Your milestones
- AI solutions that are running successfully and reliably in production.
- A well-designed model lifecycle that includes monitoring and retraining.
- AI components that demonstrably add value to products and processes.
- Reusable tooling and standards for AI development within ANVA.
- Actively contribute to knowledge sharing and the growth of the internal AI team.
Requirements
- Bachelor's or Master's degree in Computer Science, AI, or Data Science.
- Experience in developing and implementing machine learning or generative AI solutions.
- Practical knowledge of LLMs, embeddings, and evaluation methods.
- Experience integrating AI components into production environments.
- Experience with cloud-native development (preferably AWS).
- Experience with APIs and CI/CD pipelines.
- Strong analytical skills, excellent communication skills, and the ability to work well with others.
- Takes ownership of deliverables and maintains high quality standards.
