Senior ai engineer - java, llm, rag, microservices | hyderabad

Senior AI Engineer

Java · LLM · Gen AI · Microservices · Graph QL · Data Structures & Algorithms

Job Description · Full-time

Company overview

Cornerstone On Demand 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 Graph QL), 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 Graph QL 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.

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 & Graph QL APIs. Strong experience in Graph QL 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 (Postgre SQL/My SQL) and No SQL databases (Mongo DB, 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/Rabbit MQ). 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 (Open AI, 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