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Salary
≈ $12k – $29k per year (Estimated)
Location
In office (Hyderabad)
Seniority
Junior · 1+ year exp

Confirmed on the employer's own hiring board on Oct 12, 2026. First seen by Alion on Oct 6, 2026. Cornerstone OnDemand scores A on the Alion truth index.

Overview
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Cornerstone OnDemand is a Santa Monica, California software company that sells a cloud platform for workforce readiness, covering learning, talent development, skills intelligence and compliance training with AI agents. Founded in 1999 and taken private by Clearlake Capital in 2021, it serves employers worldwide and runs large engineering and support hubs in Hyderabad and Pune in India, Krakow in Poland and Heredia in Costa Rica. It hires AI engineers and scientists, forward deployment and solution engineers, SDETs, technical consultants, product support engineers, instructional designers and sales staff.

AI Engineer - Java GenAI Location: Hyderabad Experience: 1-2 Years Employment Type: Full-Time About the Role: We are looking for a motivated AI Engineer with 1-2 years of experience who has strong hands-on expertise in Java and Spring Boot and an interest in building modern AI-powered applications. The ideal candidate will work closely with senior engineers and AI teams to develop scalable backend services and contribute to RAG applications, AI workflows, data processing pipelines, and enterprise AI integrations. This role is ideal for a software engineer with a strong Java foundation who wants to build expertise in Generative AI, LLMs, RAG, and AI application development.

In this role you will… Develop and maintain scalable backend services using Java and Spring Boot. Build REST APIs and backend components for AI-powered enterprise applications. Contribute to the development of Retrieval-Augmented Generation (RAG) applications.

Work with vector databases/search technologies to support semantic search and retrieval. Develop data ingestion and processing workflows for AI applications. Implement structured JSON-based inputs and outputs, including schema validation and error handling.

Integrate AI services with enterprise databases, APIs, and backend systems. Contribute to AI orchestration and agentic workflows under the guidance of senior engineers. Write clean, maintainable, testable, and well-documented code.

Apply object-oriented programming and established software design patterns. Participate in code reviews, debugging, performance optimization, and production support. Work with cloud-based deployments and containerized applications on AWS.

You’ve got what it takes if you have… Strong Java and Spring Boot fundamentals are essential. Good problem-solving and debugging skills. Ability to understand existing systems and contribute to production-grade applications.

Strong interest in Generative AI and emerging AI technologies. Willingness to learn new AI frameworks, tools, and cloud technologies. Good communication and collaboration skills.

Ability to work effectively with senior engineers, architects, and AI/ML teams. Java Backend Development - Mandatory 1-2 years of hands-on software development experience. Strong programming skills in Java.

Good hands-on experience with Spring / Spring Boot. Strong understanding of: Object-Oriented Programming. Collections and Exception Handling.

Java Streams and Lambda expressions. REST APIs. Multithreading and concurrency basics.

Dependency Injection. Spring Boot application development. Understanding of common design patterns and clean coding practices.

Experience with unit testing using frameworks such as JUnit and Mockito. Database - Mandatory: Good knowledge of relational databases such as PostgreSQL or MySQL. Strong understanding of SQL, joins, indexing, and query optimization basics.

Exposure to MongoDB or another NoSQL database. AI / GenAI Basic to good understanding of Generative AI and LLM concepts. Understanding of RAG concepts, including: Document ingestion Chunking Embeddings Vector search Retrieval Prompt construction Understanding of prompt engineering and structured LLM outputs.

Interest in learning and working with AI agents and agentic workflows. Cloud DevOps Basic hands-on experience with AWS services. Understanding of cloud deployment concepts and containerized applications.

Exposure to Docker and CI/CD pipelines is preferred. Familiarity with services such as AWS ECS, EKS, Lambda, S3, or similar services is a plus. #LI-Onsite

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