
Manager - Digital Fabric
Tata Communications
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
