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Artificial Intelligence Architect

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Onsite

Artificial Intelligence Architect

Coforge

Artificial Intelligence Architect

Skills

Google Cloud PlatformSQL QueriesData EngineeringDeep LearningDockerPythonMicroservicesPyTorchTensorFlowData AnalysisMachine LearningAIAWSKubernetesNLP / Natural Language ProcessingComplianceRegulatory ComplianceAzure

1 month ago

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Important information


Contract type:

Permanent

Salary:

₹3,500,000 – ₹5,000,000 / year

Location:

Noida, Uttar Pradesh, India

Work mode:

Onsite

Published on:

17 September 2026

What they need


AI Architect

Job Description:

Experience: 12 to 16 Years

Job Location: Greater Noida, Pune & Hyderabad

Mandatory Skill: Generative AI (GenAI) , Large Language Models (LLMs) , Retrieval Augmented Generation (RAG), Solution Architecture / Enterprise Architecture, Designing scalable AI/ML solutions, Azure (Preferred) / AWS / GCP, LangChain or LlamaIndex & Machine Learning fundamentals.

Role Overview

We at Coforge are seeking an AI Architect to lead the design, development, and implementation of enterprise-scale Artificial Intelligence solutions. The ideal candidate will define AI strategy, architect scalable AI/ML platforms, drive GenAI adoption, and collaborate with business and technology stakeholders to deliver innovative AI-powered solutions.

The AI Architect will be responsible for establishing AI best practices, selecting appropriate technologies, ensuring governance and security compliance, and mentoring engineering teams throughout the AI lifecycle.

Key Responsibilities

  • Define enterprise AI strategy, architecture standards, and AI adoption roadmap.
  • Design end-to-end AI/ML and Generative AI solutions aligned with business objectives.
  • Architect scalable AI platforms leveraging cloud-native technologies.
  • Lead design discussions for LLM, RAG, Agents, NLP, Computer Vision, Predictive Analytics, and Machine Learning initiatives.
  • Build AI reference architectures, reusable frameworks, and solution accelerators.
  • Evaluate and integrate AI platforms, models, vector databases, and MLOps solutions.
  • Establish AI governance, security, responsible AI, and regulatory compliance standards.
  • Collaborate with business stakeholders to identify AI use cases and value realization opportunities.
  • Define data architecture requirements, model deployment strategies, and performance optimization approaches.
  • Guide engineering teams through AI solution implementation, deployment, and production support.
  • Lead proof-of-concepts (POCs), innovation initiatives, and client-facing AI workshops.
  • Stay updated with emerging AI technologies, frameworks, and industry trends.

Artificial Intelligence & Machine Learning

  • Machine Learning (Supervised & Unsupervised Learning)
  • Deep Learning
  • Generative AI
  • Large Language Models (LLMs)
  • Retrieval-Augmented Generation (RAG)
  • AI Agents / Autonomous Agents
  • NLP (Natural Language Processing)
  • Prompt Engineering
  • Model Fine-tuning
  • Computer Vision (preferred)

AI Platforms & Frameworks

  • OpenAI / Azure OpenAI
  • LangChain
  • LlamaIndex
  • Hugging Face
  • TensorFlow / PyTorch
  • Scikit-learn

Cloud Platforms

  • Microsoft Azure (Preferred)
  • AWS
  • Google Cloud Platform (GCP)

Data & Architecture

  • Data Lake / Data Warehouse Architecture
  • Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS)
  • Knowledge Graphs
  • API & Microservices Architecture
  • Event-Driven Architecture

DevOps / MLOps

  • MLflow
  • Azure ML
  • Kubeflow
  • Docker
  • Kubernetes
  • CI/CD Pipelines

Programming

  • Python (Mandatory)
  • SQL
  • REST APIs

Preferred Skills

  • Multi-Agent Frameworks (CrewAI, AutoGen)
  • AI Governance & Responsible AI
  • FinOps for AI Workloads
  • Data Engineering
  • Insurance, Banking, Healthcare, or Retail domain experience
  • Experience building enterprise AI Centers of Excellence (CoE)

Education / Qualification: BE/ B.Tech / BCA / B.Sc. / M.CA / M.TECH / Any Graduate.

Please share your profile at [email protected]

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