Core Requirement

experienced AI Architect with a proven track record of designing, building, and delivering enterprise-grade AI solutions on AWS. Hands-on architecture and production delivery experience with Generative AI and Agentic AI systems.

Key Responsibilities

- Architect and lead the design of scalable, secure, and production-ready AI platforms on AWS.
- Define end-to-end AI solution architectures, including LLM integration, agent orchestration, RAG, APIs, and cloud infrastructure.
- Design and implement Agentic AI workflows involving tool usage, planning, reasoning, memory, and multi-agent collaboration.
- Establish architecture standards, governance, security, observability, and operational best practices for AI applications.
- Collaborate with business and engineering teams to translate business requirements into AI-driven solutions.
- Drive technical decisions, technology selection, and architecture reviews across AI initiatives.

Must-Have Skills

- 10+ years of software engineering/architecture experience with recent focus on AI/GenAI solutions.
- Solid hands-on expertise in Python for AI application and backend development.
- Proven experience architecting and deploying AI solutions using Amazon Bedrock in production environments.
- Extensive experience with AWS CDK and Infrastructure as Code practices.
- Deep understanding of Agentic AI architectures, including orchestration, tool integration, workflow automation,



and autonomous agents.
- Strong experience designing RESTful APIs, microservices, and event-driven systems.
- Expertise with AWS cloud-native services and distributed application architectures.
- Experience designing highly scalable, secure, and resilient enterprise platforms.

Preferred Skills

- Experience with agent frameworks such as LangChain, LangGraph, Strands, CrewAI, AutoGen, or similar.
- Hands-on experience with AWS Lambda, Step Functions, API Gateway, EventBridge, SQS, and SNS.
- Knowledge of TypeScript for AWS CDK and cloud application development.
- Experience with RAG architectures, vector databases, knowledge retrieval systems, and enterprise search.
- Familiarity with AI governance, model evaluation, observability, prompt engineering, and responsible AI practices.
- Experience integrating AI capabilities into enterprise applications and business workflows.

Key Evaluation Criteria

- Demonstrated ownership of production AI architecture and delivery on AWS.
- Ability to design end-to-end Agentic AI and Generative AI platforms.
- Strong architecture leadership, stakeholder management, and technical decision-making skills.
- Experience scaling AI solutions from concept to enterprise-wide adoption.
- Strong understanding of cloud security, compliance, performance optimization, and operational excellence

📌 AI Architect-AWS Bedrock (Karnataka)
🏢 Sonata Software
📍 Karnataka