AI Engineer

Role overview

AI Engineer at Cornerstone OnDemand

In this role, you will… Design and build features for our AI Backend service on AWS to build scalable APIs for AI model deployment and integration.

Responsibilities

• Build and improve our LLM integration layer, including text-to-SQL pipelines, streaming agent responses and defining AI solution standards.

Required qualifications

• 2–4 years of experience building production backend services in Java and/or Python.
• Solid understanding of REST API design, distributed systems, async programming, and service-oriented architecture.
• Experience integrating LLMs into production systems.
• Familiarity with at least one vector database or semantic search system (Weaviate, Pinecone, pgvector, etc.) Experience with containerized deployments — Docker and Kubernetes Strong engineering fundamentals: you care about test coverage, code review quality, and observable, maintainable systems.

Preferred qualifications and skills

• Exposure to cloud platforms (Azure, AWS, or GCP) Familiarity with tools like Git, REST APIs, or basic data processing Experience with prompt engineering or experimenting with LLMs (ChatGPT, Copilot, etc.) Personal or academic projects involving AI or automation #LI-onsite

Employment details

• Location: Hyderabad [India]

About the employer

• AI Engineer Cornerstone OnDemand is looking for a motivated AI Engineer who will lead the building of real-world experience with AI technologies using AWS, Claude, and Generative AI tools.

Additional role details

• You will be responsible for building intelligent automation solutions, implementing AI models and creating custom Gen AI applications that enhance business processes and drive impact across the organizations of the world.
• Own the full lifecycle of backend features: design, implementation, testing, code review, and production monitoring.
• Extend our RAG architecture on Weaviate: hybrid vector + keyword search, ingestion pipelines, and embedding-based semantic caching.
• Participate in architecture discussions, technical design reviews, and cross-team collaborations with data science, product, and platform engineering.
• You’ve Got What It Takes If You Have…