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Tata Communications

Manager - Digital Fabric

Tata Communications

New Delhi, IndiaMidFull-timeOther Sign in for match

About the role

Role Overview

Threadspan is seeking a visionary and hands-on AI Architect / Principal AI Engineer to lead the design, development, and deployment of enterprise-grade Artificial Intelligence solutions. The ideal candidate will possess deep expertise in AI/ML technologies, Generative AI, LLMs, Agentic AI frameworks, cloud-native architectures, and enterprise application integration.

This role will drive AI strategy, architect scalable intelligent systems, and collaborate with business stakeholders to transform complex business challenges into innovative AI-powered solutions.

Key Responsibilities

AI Strategy & Architecture

  • Define and drive the organization's AI technology roadmap and architecture standards.
  • Design scalable, secure, and production-ready AI platforms and solutions.
  • Evaluate emerging AI technologies, models, frameworks, and tools for enterprise adoption.
  • Provide technical leadership for AI product development and innovation initiatives.

Generative AI & Large Language Models

  • Architect and implement solutions leveraging: OpenAI GPT Models
  • Azure OpenAI Services
  • Anthropic Claude
  • Google Gemini
  • Open Source LLMs (Llama, Mistral, Falcon, Phi)

Design and implement RAG (Retrieval-Augmented Generation) architectures.Develop AI Agents and Multi-Agent systems using frameworks such as:

  • LangChain
  • LangGraph
  • CrewAI
  • AutoGen
  • Semantic Kernel

Machine Learning & Data Science

  • Design end-to-end Machine Learning pipelines.
  • Develop predictive, recommendation, classification, and forecasting models.
  • Build MLOps frameworks for model deployment, monitoring, governance, and lifecycle management.
  • Establish data quality, model validation, and AI governance practices.

Enterprise AI Integration

  • Integrate AI capabilities into ERP, CRM, HRMS, and enterprise applications.
  • Design API-driven AI platforms and microservices architectures.
  • Develop intelligent automation and workflow orchestration solutions.
  • Enable chatbot, copilot, recommendation engine, and document intelligence capabilities.

Cloud & Platform Engineering

  • Architect AI solutions on: Microsoft Azure
  • AWS
  • Google Cloud Platform

Design scalable containerized deployments using:

  • Docker
  • Kubernetes
  • Azure AKS / AWS EKS

Implement distributed computing and vector database architectures.

Data Engineering & Knowledge Systems

  • Design enterprise knowledge management and semantic search solutions.
  • Build AI-powered search platforms using: Azure AI Search
  • Elasticsearch
  • Apache Solr
  • Pinecone
  • Weaviate
  • ChromaDB

Create data pipelines for structured and unstructured data processing.

Leadership & Collaboration

  • Partner with business leaders to identify AI transformation opportunities.
  • Lead architecture reviews and technical governance forums.
  • Mentor AI engineers, software developers, and data scientists.
  • Establish AI development best practices, standards, and governance models.

Technical Skills

Artificial Intelligence & Generative AI

  • Generative AI
  • Large Language Models (LLMs)
  • AI Agents & Multi-Agent Systems
  • Prompt Engineering
  • Retrieval-Augmented Generation (RAG)
  • AI Orchestration Frameworks
  • Model Fine-Tuning
  • AI Evaluation Frameworks

Machine Learning & Data Science

  • Machine Learning Algorithms
  • Deep Learning
  • NLP
  • Computer Vision (Preferred)
  • MLOps
  • Model Monitoring & Governance

Programming Languages

  • Python (Expert Level)
  • Java
  • SQL
  • JavaScript
  • C# (.NET Preferred)

AI Frameworks

  • LangChain
  • LangGraph
  • Semantic Kernel
  • LlamaIndex
  • CrewAI
  • AutoGen
  • Hugging Face

Cloud Platforms

  • Azure AI Services
  • Azure OpenAI
  • AWS Bedrock
  • Google Vertex AI

Databases & Vector Stores

  • SQL Server
  • PostgreSQL
  • MongoDB
  • Pinecone
  • ChromaDB
  • Weaviate
  • Elasticsearch

DevOps & MLOps

  • Jenkins
  • GitHub Actions
  • Azure DevOps
  • Docker
  • Kubernetes
  • Terraform

Qualifications

  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field.
  • 12-20+ years of software engineering experience with at least 5+ years in AI/ML and Generative AI solutions.
  • Proven experience delivering enterprise AI solutions in production environments.
  • Strong understanding of enterprise architecture, cloud computing, and data engineering.

Preferred Experience

  • AI-powered ERP and enterprise platform modernization.
  • Microsoft Copilot, Azure AI Foundry, and Azure OpenAI implementations.
  • Conversational AI and enterprise chatbot development.
  • Intelligent document processing and knowledge management solutions.
  • AI governance, responsible AI, and model risk management frameworks.

Required Skills

  • artificial intelligence
  • llmops
  • aiops
  • intelligent automation
  • retrieval augmented generation
  • langchain
  • generative ai
  • large language models