Manager - Digital Fabric

Tata Communications; New Delhi; On-site; INR 400,000 - 800,000; Full time

Job summary

Threadspan is seeking a visionary AI Architect to lead design, development, and deployment of enterprise-grade AI solutions. The role demands deep expertise in Generative AI, LLMs, agentic frameworks, and cloud-native architectures for scalable enterprise adoption.

The candidate will drive AI strategy, architect intelligent systems, and collaborate with business stakeholders to turn complex challenges into AI-powered outcomes across ERP, CRM, HRMS, and other enterprise apps.

Qualifications

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

Responsibilities

• Define and drive AI technology roadmap and architecture standards.
• Design scalable, secure, production-ready AI platforms and solutions.
• Evaluate emerging AI technologies, models, frameworks, and tools for enterprise use.
• Provide technical leadership for AI product development and innovation initiatives.
• Architect and implement solutions leveraging OpenAI GPT Models, Azure OpenAI, Claude, Gemini.
• Create RAG architectures and build AI Agents / Multi-Agent systems with LangChain, LangGraph, CrewAI, AutoGen.

Skills

AI Architect

LLMs

MLOps

Python

Cloud Architect

Education

Bachelor's or Master's in CS/AI

Tools

LangChain

LangGraph

Semantic Kernel

AutoGen

Hugging Face

Azure OpenAI

Azure AI Services

Weaviate

Pinecone

Job description

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.