AI Engineering Architect

Infosys; Bengaluru; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

Infosys is seeking an innovative AI Architect in Bengaluru, Karnataka to define and own AI reference architectures and architect scalable AI solutions. Ideal candidates will have a Bachelor's degree in Engineering and expertise in LLMs, Kubernetes, and cloud native technologies. The role involves integrating AI capabilities into enterprise systems and collaborating with Quality Engineering teams to embed AI into various frameworks. A strong focus on performance and reliability in architecture is essential.

Qualifications

• Expertise in LLM and Retrieval Augmented Generation technologies.
• Strong knowledge of Kubernetes, Docker, and microservices.
• Experience with AI orchestration and enterprise system integration.

Responsibilities

• Define and own AI reference architectures.
• Architect scalable solutions using LLMs and AI pipelines.
• Integrate AI capabilities into enterprise systems.

Skills

Python

Kubernetes

Generative AI

AI Architecture Engineering

Multi Agent Systems

Event Driven Architectures

Education

Bachelor of Engineering

Tools

AWS Bedrock

Azure OpenAI

Docker

Job description

Educational Requirements

Bachelor of Engineering

Service Line

Infosys Quality Engineering

Responsibilities

• AI Architecture Engineering
• Define and own AI reference architectures for generative AI, agentic systems, and AI augmented applications
• Architect scalable solutions using LLMs, multi agent systems, orchestration frameworks, and AI pipelines
• Design AI platforms supporting model serving, prompt management, RAG, and workflow orchestration
• Establish architectural standards for performance, scalability, reliability, and cost efficiency
• Platform Engineering Integration
• Build reusable AI components for LLM integration, vector search, embeddings, and inference services
• Enable secure and scalable deployment using Kubernetes, serverless platforms, and CI/CD pipelines
• Integrate AI capabilities into enterprise systems using APIs, SDKs, and event driven architectures
• Collaborate with QE teams to embed AI into test automation, test data generation, and intelligent validation

Technical and Professional Requirements

LLM AND (RAG OR "Retrieval Augmented Generation") AND (LangChain OR LangGraph OR CrewAI OR AutoGen) AND Python AND Kubernetes, Agentic AI OR "Multi Agent Systems" OR"Autonomous Agents" OR"AI Orchestration", (AWS Bedrock OR Azure OpenAI OR Vertex AI) AND (Kubernetes OR Docker) AND (Microservices OR Cloud Native)

Preferred Skills

• Technology->Open System->Open System- ALL->Python
• Technology->AI Hyperscalers->Azure Agentic AI Services->Azure NLP
• Technology->AI Hyperscalers->Google Agentic AI Services->GCP
• Technology->Agentic AI->Google Cloud
• Contact Center AI
• Technology->AI Hyperscalers->AWS Agentic AI Services->AWS Neuron
• Technology->Machine Learning->Generative AI->retrieval augmented generation (rag)
• Technology->AI Engineering->AI/ML Solution Architecture and Design
• Technology->Agentic AI->Agent Engineering
• Technology->AI Engineering->Model Deployment (Kubernetes)
• Technology->Agentic AI->AgentOps