Senior Al Engineer | Java, LLM & Gen AI

Senior AI Engineer | Hyderabad | Java, LLM, Gen AI | Hybrid Java LLM Gen AI Microservices GraphQL Data Structures Algorithms

Cornerstone OnDemand builds intelligent products that help organizations learn and perform  value ownership, clarity, and pragmatic engineering- shipping reliable systems that blend modern AI with solid backend discipline. This role sits at the intersection of platform engineering and applied AI.

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

• 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, No
  
  SQL, 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.

• 5-8 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 No
  
  SQL 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.

• 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 platforms.

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