Senior AI Engineer - Java, LLM, RAG, Microservices | Hyderabad

Senior AI Engineer

Java · LLM · Gen AI · Microservices · GraphQL · Data Structures & Algorithms

Job Description · Full-time

Company overview

Cornerstone OnDemand builds intelligent products that help organizations learn and perform at scale. We 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.

The Role

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.

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 Have

• 3y–6y 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 platforms