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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 creative 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.

📌 Manager - Digital Fabric (India)
🏢 Tata Communications
📍 India