HyperWrkan Albireo Recruiters platform
Confidential · Technology

AI Infrastructure Architect – CL 8

  • Pune · Office
  • 7–15 yrs
  • CTC Not disclosed
  • Full-time
  • Notice ≤ 90 days
  • Posted 28 Sep 2026
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A technology company in Pune is hiring an AI Infrastructure Architect with 7.5 to 15 years of experience. The role covers designing scalable AI platforms for agents and LLM workloads, working on cloud, containers and infrastructure-as-code. The work is in the office. Apply on hyperwrk.com.

The role

The company needs an AI Infrastructure Architect to design, build and optimise scalable infrastructure for enterprise AI and agentic AI workloads. You will act as the subject matter expert for AI infrastructure and AI agent and workflow integration, and lead technical decisions across several delivery teams.

A typical day involves reviewing designs for AI agent workflows, tool and API integrations, orchestration layers and model-serving setups. You will evaluate performance, latency, cost and capacity of AI workloads, and work with cloud, DevOps, data engineering, security and business teams. You will also support build-versus-buy and vendor decisions, troubleshoot complex issues, and mentor junior team members.

We are looking for hands-on experience with AI agent solutions and orchestration frameworks, and a sound understanding of LLM patterns such as retrieval-augmented generation, embeddings, vector databases and model routing. You should have designed AI infrastructure for scale, reliability and security, and worked with AWS, Azure or GCP, Docker, Kubernetes, Terraform or similar tools, and CI/CD practices. Experience with Kafka or other event-streaming tools, monitoring and observability, and strong stakeholder communication will help.

The role is full-time and based in Pune. It is an in-office position. The experience band is 7.5 to 15 years, and candidates with a notice period of up to 90 days are considered.

To apply, sign in on hyperwrk.com and apply in one step. A recruiter at Albireo reads every application.

Must have

  • Strong hands-on experience in AI Agents & Workflow Integration
  • Retrieval-Augmented Generation (RAG), embeddings and vector databases
  • Experience with cloud infrastructure such as AWS, Azure, or GCP
  • Strong knowledge of Docker, Kubernetes, containerized deployments
  • Strong knowledge of Docker, Kubernetes, containerized deployments
  • infrastructure-as-code tools such as Terraform, CloudFormation, or equivalent
  • DevOps practices, CI/CD pipelines, automated deployment
  • GPU or accelerated compute, distributed workloads, compute clusters
  • monitoring, observability, logging, performance tuning, capacity planning

Nice to have

  • LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, or similar AI-agent frameworks
  • NVIDIA GPU infrastructure, CUDA, GPU scheduling
  • MLOps and LLMOps practices, including MLflow
  • Kafka, RabbitMQ, Airflow, Temporal, Camunda, or similar platforms
  • AWS SageMaker/EKS, Azure AI Foundry, Azure ML, Google Vertex AI

What happens after you apply

The recruiter working this role reads your application. If it fits, they call you before anything is shared with the company. You see every stage in your account, in plain words.