AI Engineer

Cornerstone Research; Hyderabad; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Cornerstone is seeking an AI Engineer with 1–2 years of hands-on experience in Java and Spring Boot to build scalable backend services and AI-powered applications in Hyderabad.

You will collaborate with AI teams on RAG applications, vector databases, embeddings, and cloud deployments on AWS, with opportunities to explore GenAI, LLM concepts, and agent-based workflows.

Qualifications

• 1–2 years of hands-on software development experience.
• Strong Java and Spring Boot fundamentals.

Responsibilities

• Develop and maintain scalable backend services using Java and Spring Boot.
• Build REST APIs for AI-powered enterprise applications.
• Contribute to Retrieval-Augmented Generation (RAG) applications.
• Work with vector databases and semantic search.
• Develop data ingestion and processing workflows for AI apps.
• Integrate AI services with enterprise databases, APIs, and backends.
• Participate in reviews, debugging, and production support.
• Work with AWS-based cloud deployments and containers.

Skills

Java

Spring Boot

REST APIs

SQL

PostgreSQL/MySQL

MongoDB

AWS

Docker/CI-CD

RAG/GenAI

LLMs

Tools

Java tooling

Spring Boot tooling

Vector search

Cloud deployments

Job description

We're looking for a

AI Engineer

This role is Office Based,Hyderabad Office

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.

Inthis 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’vegot 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:

1. Object-Oriented Programming.
2. Collections and Exception Handling.
3. Java Streams and Lambda expressions.
4. REST APIs.
5. Multithreading and concurrency basics.
6. Dependency Injection.
7. 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:

1. Document ingestion
2. Chunking
3. Embeddings
4. Vector search
5. Retrieval
6. 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

Our Culture:

Spark Greatness. Shatter Boundaries. Share Success. Are you ready? Because here, right now – is where the future of work is happening. Where curious disruptors and change innovators like you are helping communities and customers enable everyone – anywhere – to learn, grow and advance. To be better tomorrow than they are today.

Who We Are:

At Cornerstone, we believe in AI that works in the service of people, amplifying their judgment to drive high‑performing, future‑ready organizations forward. Cornerstone Workforce AI™, the intelligence platform for workforce readiness, brings together workforce and labor market data into a proprietary Cornerstone People Graph™, translating signals into intelligence, targeting learning where it matters, developing critical skills, and surfacing hidden talent. Delivered as an open, enterprise platform across whatever application your people work in every day, Cornerstone Workforce AI is built for scale, security, and trust, with certified AI guardrails. As an industry leader, Cornerstone is helping approximately 7,000 organizations, 140M+ users, across 186 countries build continuous workforce readiness.