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AI / ML Engineering or Architecture

  • Source: Naukri
  • Conqueri Technologies India
  • $52,301.97 to $73,222.76 /yr
  • On-site
  • Hyderabad
  • Full-Time
  • Mid level

Job Description

Designation : AI/ML Architect

Location: Hyderabad (Onsite 5 Days/Week)
Experience: 10-18 Years
Positions:(Contractor to Hire) 4
Employment Type: Contractor / Consultant
Notice Period: Immediate Joiners or Max 2 Weeks

Role Summary

We are looking for an experienced AI/ML Architect to lead the design, development, deployment, and optimization of enterprise AI/ML and Agentic AI solutions. The ideal candidate should have strong hands-on expertise in AI architecture, LLMs, Python, LangChain, and LangGraph, with experience delivering scalable AI solutions on cloud platforms.

Key Responsibilities

  • Design and deliver enterprise AI/ML and Agentic AI solutions.
  • Build and deploy LLM, RAG, and multi-agent AI applications.
  • Develop AI workflows using LangChain and LangGraph.
  • Lead architecture, code reviews, and technical guidance for engineering teams.
  • Implement MLOps/LLMOps pipelines and AI governance best practices.
  • Collaborate with cross-functional teams and client stakeholders.

Mandatory Skills

  • AI/ML Architecture
  • Large Language Models (LLMs)
  • Python
  • LangChain
  • LangGraph
  • RAG & Vector Databases
  • MLOps / LLMOps
  • GCP (Vertex AI) and/or Azure AI
  • Docker & Kubernetes

Required Experience

  • 10+ years in Software Engineering/Architecture with 5+ years in AI/ML delivery.
  • Hands-on experience with PyTorch, TensorFlow, or Scikit-learn.
  • Experience with MLflow, Airflow, Kubeflow, Argo, or KServe.
  • Strong knowledge of GCP/Azure AI services and cloud-native architectures.
  • Excellent communication and stakeholder management skills.

Immediate joiners or candidates who can join within 2 weeks are highly preferred.

Skills

  • agentai
  • LangChain
  • LangGraph
  • Python
  • google-cloud-platform
  • vertex
  • microsoft-azure
  • Docker
  • Kubernetes
  • PyTorch
  • Tensorflow
  • Scikit-learn
  • ml-flow
  • mlflow
  • Airflow
  • apache-airflow
  • kubeflow
  • argo

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