Role overview
This is a rare opportunity to build AI systems that will have real enterprise and customer impact at global scale, within an organization investing meaningfully in modern AI capabilities.
Confidential search. Serious momentum. High visibility.
What you'll work on
- Design, build, and deploy production-grade AI/ML solutions on cloud platforms (Azure, AWS, or GCP).
- Develop LLM-based applications, including RAG (retrieval-augmented generation), agent workflows, and tool-based reasoning systems.
- Build scalable AI services, APIs, and pipelines that integrate into enterprise platforms and business workflows.
- Partner with engineering, data, and product stakeholders to translate business needs into practical technical solutions.
- Implement strong engineering standards for deployment, monitoring, reliability, and iteration.
- Contribute to MLOps practices using tools such as Docker, Kubernetes, MLflow, CI/CD, and observability tooling.
- Support model evaluation and continuous improvement to ensure quality, performance, and measurable impact.
What we're looking for
- Experience with RAG pipelines, embeddings, semantic search, and vector databases (FAISS, Pinecone, Weaviate, pgvector, etc.).
- Familiarity with LangChain, LlamaIndex, or open-source orchestration frameworks.
- Experience with evaluation frameworks, monitoring, and responsible AI practices.
- Experience optimizing inference for performance, latency, and cost.
- Advanced degree in AI/ML, Computer Science, Data Science, or related field (great plus but not required).
Tags & focus areas
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