Principal Solution Architect - AI/ML

National e-Governance Division, Digital India Corporation; India; On-site; INR 3,500,000 - 5,500,000; Full time

Job summary

National e-Governance Division, Digital India Corporation is seeking an seasoned AI/ML Architect to design end-to-end AI solution architectures that embed ML capabilities into NeGD and related government applications.

You will define integration standards, APIs, and interoperability with Digital India platforms, oversee data flow, security, privacy, and Responsible AI implementation, and guide architecture governance across Data Science, MLOps and Engineering teams.

Qualifications

• Bachelors or higher in CS/IT/AI or related field.
• Certifications in leading cloud AI platforms preferred.
• Research papers or significant open-source contributions preferred.

Responsibilities

• Design end-to-end AI/ML solution architectures embedding AI capabilities into NeGD and government apps.
• Define integration standards, APIs, and interoperability frameworks with Digital India platforms.
• Oversee data flow, security, privacy, and Responsible AI across solutions.
• Architect and oversee AI app integrations with current enterprise apps and platforms.
• Evaluate cloud-native and on-premise deployment models per MeitY guidelines.
• Provide architectural leadership for scalability, maintainability, and compliance.
• Collaborate with DS, MLOps, and Engineering for governance.
• Conduct periodic architectural reviews and mentor development teams.

Education

B.Tech / M.Tech / MS / Ph.D. in Computer Science, Information Technology, Artificial Intelligence, or a related technical field.

Tools

AWS Bedrock

SageMaker

Lambda

API Gateway

S3

Azure OpenAI Service

ML Studio

AKS

Vertex AI

BigQuery

Cloud Storage

TensorFlow

PyTorch

Hugging Face Transformers

LangChain

Prompt-engineering

RBAC

PostgreSQL

MySQL

MongoDB

DynamoDB

Pinecone

Weaviate

Job description

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 Professional, 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 professional experience.
• At least 5 years in AI/ML system design
• Proven experience designing and deploying multi-component AI solutions for government or enterprise environments.

Key Responsibilities:

1. Design and implement end-to-end solution architectures embedding AI/ML capabilities into NeGD and allied government applications.

2. Define integration standards, APIs, and interoperability frameworks between AI systems and existing Digital India platforms.

3. Oversee data flow architecture, security, privacy, and Responsible AI implementation across solutions.

4. Architect and oversee integration of AI applications with NeGDs current enterprise applications and digital platforms.

5. Evaluate and recommend cloud-native and on-premises deployment models in alignment with MeitY guidelines.

6. Provide architectural leadership, ensuring scalability, maintainability, and compliance with MeitY and NIC technical standards.

7. Collaborate with Data Science, MLOps, and Engineering teams for unified architecture governance.

8. 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)