Lead Al Engineer

Cornerstone; Hyderabad; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

Cornerstone in Hyderabad seeks a Lead AI Engineer to architect, develop, and scale enterprise AI infrastructure and content processing pipelines. You will lead the technical design for RAG frameworks, LLM gateways, and intelligent agent workflows, ensuring robust data pipelines in an AWS cloud ecosystem.

The role emphasizes leadership, scalable architecture, and strict JSON validation to guarantee parsing stability across systems.

Qualifications

• 5-8 years of professional software engineering experience in enterprise-grade systems.
• Deep hands-on expertise in Java and Spring/Spring Boot.
• Good working knowledge of Python for AI/ML integrations.
• Strong knowledge of PostgreSQL/MySQL and MongoDB.
• Experience with AWS cloud services and containerized deployments.
• Experience building scalable RAG applications and LLM orchestration.

Responsibilities

• Lead AI architecture, strategy, and design for content ingestion and enrichment pipelines.
• Design, deploy, and optimize retrieval-augmented generation frameworks and LLM gateways.
• Build and orchestrate multi-agent platforms and workflows for enterprise use.
• Drive Model Context Protocol implementation to standardize integrations.
• Architect reliable LLM generation pipelines with strict JSON-based validation.
• Mentor teams and guide cloud-based deployment and infra planning.

Skills

Java

Spring/Spring Boot

Python

Object-oriented design

Enterprise integration patterns

AWS

RAG applications

JSON data validation

Tools

PostgreSQL

MySQL

MongoDB

Job description

Job Title:Lead AI Engineer

Location: Hyderabad

About theRole:

We are seeking an experienced Lead AI Engineerto architect, develop, and scale our enterprise AI infrastructure and contentprocessing pipelines. You will lead the technical design of AI systems,focusing on Retrieval-Augmented Generation (RAG) frameworks, LLM gateways, andintelligent agentic workflows. As a technical leader, you will ensure our AIdata pipelines are robust, highly structured, and seamlessly integrated intoour AWS cloud ecosystem.

In this role you will...

• AI Architecture & Strategy: Lead the architectural oversight and technical direction for content ingestion and enrichment pipelines, ensuring scalable and efficient AI integrations.
• RAG & LLM Integration: Design, deploy, and optimize advanced Retrieval-Augmented Generation (RAG) frameworks and centralized LLM gateways.
• Agentic Workflows: Build and orchestrate multi-agent platforms and workflows using modern AI integration frameworks.
• Protocol Implementation: Drive the implementation of Model Context Protocol (MCP) to standardize and streamline interactions between foundation models and enterprise backend systems.
• Data Pipeline Engineering: Architect highly reliable LLM generation pipelines, enforcing strict structured JSON outputs to guarantee schema validation and application parsing stability.
• Technical Leadership & System Design: Mentor engineering teams, apply best-in-class software design patterns, and guide infrastructure deployment planning across cloud environments.

You'vegot what it takes if you have

• Experience: 5-8 years of professional software engineering experience, with a proven track record of designing and deploying enterprise-grade systems and AI platforms.
• Programming & Frameworks (Mandatory): Deep, hands-on expertise in Java and the Spring / Spring Boot framework.
• Good working knowledge of Python is also required for AI/ML integrations and scripting.
• Database Expertise (Mandatory): Strong knowledge of both relational databases (RDBMS such as PostgreSQL or MySQL) and NoSQL databases, specifically MongoDB.
• Design Patterns (Mandatory): Extensive knowledge of object-oriented design, architectural design patterns, and enterprise integration patterns for building scalable, decoupled systems.
• Cloud Infrastructure (Mandatory): Hands-on experience with AWS cloud services, including the deployment, scaling, and management of containerized applications and data pipelines.
• AI/ML Expertise: Practical experience building scalable RAG applications, vector search optimizations, and LLM orchestration layers.
• Data Engineering: Proven ability to build resilient data ingestion workflows with a strong emphasis on JSON-based structured data validation over legacy text formats.

Good to have skills...

• Familiarity with enterprise AI toolkits (such as Google ADK).
• Experience managing regional infrastructure rollouts and navigating model availability constraints across different deployment stages.

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