Senior Al Engineer | Java, LLM & Gen AI

Senior AI Engineer | Hyderabad | Java, LLM, Gen AI | Hybrid

Java LLM Gen AI Microservices GraphQL DataStructures & Algorithms

Companyoverview

Cornerstone OnDemand builds intelligent products that helporganizations learn and perform at scale. We value ownership, clarity, andpragmatic engineeringshipping reliable systems that blend modern AI with solidbackend discipline. This role sits at the intersection of platform engineeringand applied AI.

The Role

We are looking for a Senior AI Engineer to design anddeliver backend services that power retrieval-augmented workflows, semanticsearch, and LLM-backed features. You will work across APIs (REST and GraphQL),data stores, and cloud-native infrastructurepartnering with product and MLstakeholders to bring AI capabilities safely into production.

In This Role You Will

Design, build, and operate scalable Java/Spring Boot microservices and shared platform components.
Own GraphQL schema evolution, resolvers, and performance (N+1 avoidance, batching, caching).
Integrate LLMs, embeddings, and vector search into production paths with clear observability and fallbacks.
Apply strong data structures and algorithms judgment to performance-sensitive paths (indexing, ranking, batching, and cost-aware service design).
Collaborate on data modeling and API contracts across SQL, NoSQL, and vector stores.
Champion security (OAuth2, JWT, API hardening) and reliability in distributed, event-driven systems.
Improve CI/CD, automated testing, and deployment practices for safe, frequent releases.

You Have Got What It Takes If You

58 years of experience in backend or platform engineering with strong expertise in Java.
Hands-on experience with Spring Boot, microservices architecture, REST & GraphQL APIs.
Strong experience in GraphQL schema design, resolvers, and query optimization (N+1, batching, caching).
Solid understanding of data structures, algorithms, OOP, and distributed system design.
Experience working with SQL (PostgreSQL/MySQL) and NoSQL databases (MongoDB, Redis).
Familiarity with vector databases such as Weaviate, Pinecone, or Milvus.
Practical exposure to LLMs, embeddings, and NLP concepts.
Experience with Docker, Kubernetes, and at least one cloud platform (AWS / Azure / GCP).
Understanding of asynchronous processing, event-driven systems, and messaging (Kafka/RabbitMQ).
Knowledge of security practices (OAuth2, JWT, API security).
Experience with CI/CD pipelines and automated deployments.
Preferred
Hands-on experience building RAG (Retrieval-Augmented Generation) systems.
Experience with semantic search / hybrid search (BM25 + embeddings).
Familiarity with LLM APIs (OpenAI, Bedrock, etc.) and prompt engineering.
Exposure to LLMOps / MLOps workflows.
Experience with API gateways, rate limiting, and high-scale systems.
Prior work on AI-driven products or platform