AI Engineer
About the role
- Design, develop, fine-tune, and deploy generative AI models into scalable production environments
- Build and maintain APIs and microservices using FastAPI to expose AI capabilities enterprise wide
- Collaborate with the AI Infrastructure team to architect robust LLM pipelines, including training workflows and retrieval-augmented generation (RAG) systemsIntegrate AI solutions into enterprise applications using secure, cloud-native architectures and best practices
- Minimum of 6+ years of experience building data‑driven software solutions
- Minimum of 3+ years of hands-on AI development experience.
- Proficiency in Python, with practical experience building applications using LLMs, embeddings, vector databases, and RAG architecture.
- Demonstrated experience with generative AI models, including multimodal models.
- Hands-on experience developing and deploying AI applications using Azure Foundry, Docker, Kubernetes, and GPU-backed compute.
- Bachelor's degree in computer science, Artificial Intelligence, or a related field, or equivalent professional experience
- Experience fine-tuning, evaluating, and deploying models using Azure-managed AI services and compute resources
- Familiarity with agent frameworks and experience deploying AI agents with tool integration, appropriate permissions, and operational safeguards
- Experience building graph-enhanced RAG and hybrid retrieval solutions using graph databases such as Neo4j, Stardog, or Azure Cosmos DB for Apache Gremlin
- Experience deploying models with low latency and high throughput, using frameworks like vLLM and other GPU model deployment tools
- Hands-on experience building CI/CD pipelines and automated testing workflows for generative AI application
- Experience with distributed training, GPU optimization, and large-scale model frameworks (CUDA, RAPIDS)
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
