Senior Principal Al Engineer

Cornerstone; Hyderabad; On-site; INR 3,500,000 - 6,000,000; Full time

Job summary

Cornerstone is seeking an experienced AI/ML software engineer to design, develop, and deploy production-grade AI agents and multi-agent systems. You will build RAG solutions, orchestrate intelligent workflows, and implement scalable REST APIs using FastAPI, with deployments on Docker/Kubernetes across AWS/Azure/GCP.

The role requires 8+ years in software engineering, strong Java and Python skills, and hands-on experience with LangGraph, LangChain, and vector databases.

Qualifications

• Bachelor's or Master's degree in computer science, AI, ML, or related field.
• 8+ years of software engineering experience.
• Minimum 3 years hands-on building AI/Generative AI apps using LLMs.
• Minimum 3 years experience developing scalable backend software and distributed systems.
• Strong proficiency in Java and Python and modern software engineering principles.
• Hands-on experience with AI orchestration frameworks such as LangGraph, LangChain, LlamaIndex, etc.
• Experience designing and implementing production-grade RAG systems, including embedding models, semantic search, hybrid search, reranking, and vector databases.
• Experience with vector databases like Milvus, Pinecone, Weaviate, OpenSearch/Elasticsearch, FAISS, or ChromaDB.
• Experience integrating and deploying applications using LLMs such as OpenAI GPT, Claude, Gemini, Llama, Mistral, Amazon Nova, or Azure OpenAI.
• Strong experience building REST APIs using FastAPI or similar Python frameworks.
• Experience with Docker and Kubernetes for deployment and orchestration.
• Experience deploying AI solutions on AWS, Azure, or GCP.
• Familiarity with CI/CD pipelines, Git, and modern DevOps practices.
• Experience with AI evaluation, prompt engineering, observability, and monitoring tools such as LangSmith, Langfuse, MLflow, OpenTelemetry, Prometheus, or Grafana.
• Strong understanding of software architecture, microservices, asynchronous programming, and distributed systems.
• Excellent problem-solving, communication, and collaboration skills in a cross-functional team.

Responsibilities

• Design, develop, and deploy production-grade AI agents and multi-agent systems using modern LLM frameworks.
• Build and optimize Retrieval-Augmented Generation (RAG) solutions for enterprise-scale applications.
• Develop intelligent workflows involving planning, reasoning, memory management, tool calling, and function calling.
• Design and implement scalable backend services and REST APIs using Python frameworks such as FastAPI.
• Integrate LLMs with enterprise systems, vector databases, APIs, and external tools.
• Deploy AI applications using Docker, Kubernetes, and cloud platforms such as AWS, Azure, or GCP.
• Optimize AI systems for latency, scalability, reliability, and cost efficiency.
• Build evaluation pipelines to measure retrieval quality, response relevance, hallucination rates, and overall LLM performance.
• Implement semantic search, hybrid search, reranking, embedding pipelines, and vector database integrations.
• Establish observability, monitoring, logging, and tracing for AI applications using industry-standard tools.
• Collaborate with product managers, software engineers, data scientists, and platform teams to deliver end-to-end AI solutions.
• Mentor junior engineers and promote AI engineering best practices, coding standards, and architectural excellence.
• Stay up to date with emerging advancements in LLMs, Agentic AI, RAG, and AI infrastructure.

Skills

Java

Python

REST API design

Problem solving

Communication

Distributed systems

Education

Bachelor's or Master's in CS/AI/related field

Tools

LangGraph

LangChain

LlamaIndex

Milvus

Pinecone

Weaviate

OpenSearch/Elasticsearch

FAISS

ChromaDB

Docker

Kubernetes

AWS/Azure/GCP

FastAPI

Job description

About Cornerstone:

Cornerstone powers the future-ready workforce with modern, AI-driven employment solutions. Our platform enables companies to develop, manage, and engage their talentunlocking growth and innovation across organizations of all sizes.

In this role you will..

• Design, develop, and deploy production-grade AI agents and multi-agent systems using modern LLM frameworks.
• Build and optimize Retrieval-Augmented Generation (RAG) solutions for enterprise-scale applications.
• Develop intelligent workflows involving planning, reasoning, memory management, tool calling, and function calling.
• Design and implement scalable backend services and REST APIs using Python frameworks such as FastAPI.
• Integrate LLMs with enterprise systems, vector databases, APIs, and external tools.
• Deploy AI applications using Docker, Kubernetes, and cloud platforms such as AWS, Azure, or GCP.
• Optimize AI systems for latency, scalability, reliability, and cost efficiency.
• Build evaluation pipelines to measure retrieval quality, response relevance, hallucination rates, and overall LLM performance.
• Implement semantic search, hybrid search, reranking, embedding pipelines, and vector database integrations.
• Establish observability, monitoring, logging, and tracing for AI applications using industry-standard tools.
• Collaborate with product managers, software engineers, data scientists, and platform teams to deliver end-to-end AI solutions.
• Mentor junior engineers and promote AI engineering best practices, coding standards, and architectural excellence.
• Stay up to date with emerging advancements in LLMs, Agentic AI, RAG, and AI infrastructure.

You've got what it takes if you have...

• Bachelor's or masters degree in computer science, Artificial Intelligence, Machine Learning, or a related technical field.
• 8+ years of overall software engineering experience.
• Minimum 3 years of hands-on experience building AI/Generative AI applications using Large Language Models (LLMs).
• Minimum 3 years of experience developing scalable backend software and distributed systems.
• Strong proficiency in Java and Python and modern software engineering principles.
• Hands-on experience with AI orchestration frameworks such as LangGraph, LangChain, LlamaIndex, etc.
• Experience designing and implementing production-grade RAGsystems, including embedding models, semantic search, hybrid search, reranking, and vector databases.
• Experience with vector databases such as Milvus, Pinecone, Weaviate, OpenSearch, Elasticsearch, FAISS, or ChromaDB.
• Experience integrating and deploying applications using LLMs such as OpenAI GPT, Claude, Gemini, Llama, Mistral, Amazon Nova, or Azure OpenAI.
• Strong experience building REST APIs using FastAPIor similar Python frameworks.
• Experience with containerization and orchestration technologies such as Dockerand Kubernetes.
• Experience deploying AI solutions on cloud platforms such as AWS, Azure, or GCP.
• Familiarity with CI/CD pipelines, Git, and modern DevOps practices.
• Experience with AI evaluation, prompt engineering, observability, and monitoring tools such as LangSmith, Langfuse, MLflow, OpenTelemetry, Prometheus, or Grafana.
• Strong understanding of software architecture, microservices, asynchronous programming, and distributed systems.
• Excellent problem-solving, communication, and collaboration skills, with the ability to work effectively in a cross-functional team environment.

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