Educational Qualification
B.Tech / M.Tech / MS / Ph.D. in Computer Science, Information Technology, Artificial
Intelligence, or a related technical field.
Certifications preferred: AWS Solutions Architect Qualified, Azure Solutions
Architect Expert, or GCP Professional Cloud Architect.
Research papers, case studies, or significant open-source contributions (are preferred)

Experience
Minimum 12+ years of total skilled experience.
At least 5 years in AI/ML system design
Proven experience designing and deploying multi-component AI solutions for government or enterprise settings.

Key Responsibilities
Design and implement end-to-end solution architectures embedding AI/ML capabilities into NeGD and allied government applications.
Define integration standards, APIs, and interoperability frameworks between AI systems and existing Digital India platforms.
Oversee data flow architecture, security, privacy, and Responsible AI implementation across solutions.
Architect and oversee integration of AI applications with NeGD’s current enterprise applications and digital platforms.
Evaluate and recommend cloud-native and on-premises deployment models in alignment with MeitY guidelines.
Provide architectural leadership, ensuring scalability, maintainability,



and compliance with MeitY and NIC technical standards.
Collaborate with Data Science, MLOps, and Engineering teams for unified architecture governance.
Conduct periodic architectural reviews and provide technical mentoring to development teams.

Technical Competencies:
Architecture: Microservices and serverless patterns, event-driven and domain-driven design, high-level data & model lifecycle architecture
Cloud: AWS (Bedrock, SageMaker, Lambda, API Gateway, S3), Azure (OpenAI Service, ML Studio, AKS), GCP (Vertex AI, Big Query, Cloud Storage), multi-cloud integration & cost optimization
AI Frameworks: TensorFlow, PyTorch, Hugging Face Transformers, Lang Chain (LLM orchestration), prompt-engineering and responsible AI practices
Data &
Storage:

SQL (PostgreSQL, MySQL), NoSQL (MongoDB, DynamoDB), vector databases (Pinecone, Weaviate) for RAG & semantic search
APIs &
Integration: REST, GraphQL, WebSocket for real-time chat/voice
Conversational AI &
Voice: Speech-to-Text and Text-to-Speech APIs (AWS Transcribe/Polly, Azure Speech), RAG/chatbot pipeline design with vector stores &
LLMs
Security &
Governance: IAM and RBAC across clouds, encryption in transit & at rest, data privacy &
AI governance (GDPR, SOC2)

📌 Principal Architect Ai New Delhi
🏢 National e Governance Division
📍 New Delhi