AI Architect with AWS - A
Summary
Senior AI Architect (10-15 yrs) at Tata Consultancy Services designing and delivering enterprise-scale Generative AI and ML solutions on AWS — Amazon Bedrock, SageMaker, RAG, AI agents and copilots. Leads architecture reviews, sets AI governance/Responsible AI standards, and drives cloud transformation while engaging business stakeholders. Roles based in Chennai, Kochi, Kolkata, or Coimbatore.
AI Architect - AWS
Experience: 10-15 Years
Location: Chennai / Kochi / Kolkata / Coimbatore
We are looking for an experienced AI Architect to design and deliver enterprise-scale Generative AI and Machine Learning solutions on AWS. The ideal candidate will have strong expertise in Amazon Bedrock, AWS AI/ML services, LLMs, RAG architectures, Agentic AI, cloud-native design, and enterprise solution architecture, along with the ability to lead technical teams and engage with business stakeholders.
Key Responsibilities
- Architect and deliver scalable, secure, and cost-efficient AI/GenAI solutions on AWS.
- Design enterprise copilots, virtual assistants, AI agents, and RAG-based applications.
- Define end-to-end architectures covering data ingestion, vector search, model serving, orchestration, monitoring, and governance.
- Evaluate and implement Foundation Models using Amazon Bedrock and AWS SageMaker.
- Establish AI architecture standards, reusable frameworks, and best practices.
- Lead architecture reviews, technical design discussions, and solution governance.
- Drive AI modernization initiatives and provide technical leadership across teams.
- Define AI security, compliance, Responsible AI, and operational frameworks.
- Collaborate with business and technology stakeholders to identify and implement AI use cases.
Mandatory Skills
- Generative AI, LLMs, Prompt Engineering
- RAG (Retrieval-Augmented Generation)
- AI Agents / Agentic AI
- Amazon Bedrock
- AWS SageMaker
- AWS Lambda, S3, API Gateway, IAM, CloudWatch
- ECS/EKS, Step Functions
- Enterprise & Solution Architecture
- Cloud-Native and Microservices Architecture
- Python, SQL, REST APIs
- LangChain, LlamaIndex, Hugging Face
- Docker, Kubernetes, CI/CD, MLOps
- Stakeholder Management and Technical Leadership
Preferred Skills
- OpenSearch and Vector Databases (Pinecone, FAISS, Weaviate)
- AWS Glue, EMR, Databricks
- Terraform / Infrastructure as Code
- Knowledge Graphs and Graph Databases
- Responsible AI and AI Governance
Preferred Certifications
- AWS Certified Solutions Architect Professional
- AWS Certified Machine Learning Engineer
- AWS Certified AI Practitioner
- TOGAF (Preferred)
Ideal Candidate Should Have Experience In
- Enterprise GenAI platform architecture
- Production-grade RAG implementations
- Multi-model AI ecosystems using Amazon Bedrock
- AI copilots and intelligent assistants
- AI governance, security, and compliance
- Large-scale cloud transformation and modernization programs
Skills
- Agentic AI
- AI
- API
- API Gateway
- AWS
- AWS Bedrock
- Aws Glue
- CI/CD
- Cloud
- Cloud Native
- CloudWatch
- Data Ingestion
- Databricks
- Docker
- ECS
- EKS
- FAISS
- Generative AI
- Hugging Face
- IAM
- Infrastructure as Code
- Kubernetes
- Lambda
- LangChain
- LlamaIndex
- LLM
- Machine Learning
- Microservices
- MLOps
- OpenSearch
- Pinecone
- Prompt Engineering
- Python
- RAG
- REST
- S3
- SageMaker
- SQL
- Stakeholder Management
- Terraform
- TOGAF
- Vector Databases
- Vector Search
- Weaviate