AI /ML Architect

AI/ML Architect

Experience:

• Minimum 812 years of total professional experience.
• At least 4-5 years in architecting enterprise-level AI/ML solutions or large-scale data systems.
  Proven experience designing and deploying multi-component AI solutions for enterprise environments.

Key Responsibilities:

1. Design and implement end-to-end solution architectures embedding AI/ML capabilities .
2. Define integration standards, APIs, and interoperability frameworks between Al 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 current enterprise applications and digital platforms.
5. Evaluate and recommend cloud-native and on-premises deployment models in alignment with prescribed guidelines.
6. Collaborate with Data Science, MLOps, and Engineering teams for unified architecture governance

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 (OpenAl Service, ML Studio, AKS), GCP (Vertex AI, BigQuery, Cloud Storage), multi-cloud integration & cost optimization

• AI Frameworks: TensorFlow, PyTorch, Hugging Face Transformers, LangChain (LLM orchestration), prompt-engineering and responsible Al 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