Role Summary :

We are seeking a highly experienced Agentic AI Solution Architect to design and scale autonomous AI systems on AWS. This role will architect multi-agent frameworks, LLM-powered decision systems, and enterprise-grade AI platforms that integrate with data warehouses, MarTech ecosystems, and business applications. The architect will define technical strategy for agent orchestration, reasoning pipelines, retrieval-augmented generation (RAG), and AI governance while ensuring security, scalability, and cost efficiency.

Key Responsibilities :

- Architect multi-agent systems using planner - executor - critic patterns and autonomous workflows.
- Design and deploy foundation models using Amazon Bedrock, SageMaker, and open-source LLMs.
- Build scalable RAG pipelines with vector databases and knowledge bases.
- Lead AWS architecture across VPC, IAM, KMS, S3, Glue, Redshift, ECS/EKS, and Step Functions.
- Develop event-driven AI automation frameworks using Lambda and EventBridge.
- Establish AI governance including explainability, bias monitoring, hallucination detection, and audit logging.
- Implement infrastructure as code using Terraform, CloudFormation, or AWS CDK.
- Integrate AI agents with enterprise data warehouses, MarTech systems, CRM platforms, and APIs.
- Define observability and telemetry standards for agent performance and reliability.
- Translate business use cases into scalable AI solution architectures.

Required Qualifications :

- 8 years of experience in cloud architecture.
- 3 years designing AI/ML systems on AWS.
- Hands-on experience with Amazon Bedrock, SageMaker, and vector databases.




- Strong Python programming skills and experience building distributed systems.
- Experience with LangChain, LlamaIndex, AutoGen, or similar agentic frameworks.
- Deep understanding of RAG architecture and semantic metadata models.

Preferred Qualifications :

- AWS Certified Solutions Architect - Skilled.
- Experience deploying production-grade agentic systems.
- Background in regulated industries such as Pharma, Healthcare, or Financial Services.
- Experience implementing AI governance and compliance frameworks.

Technical Stack :

- Foundation Models: Amazon Bedrock, OpenAI APIs, HuggingFace
- Orchestration: AWS Step Functions, Lambda, EventBridge
- Storage: S3, Redshift, DynamoDB
- Vector Databases: OpenSearch, Pinecone
- Data Processing: Glue, EMR
- Deployment: ECS, EKS
- Observability: CloudWatch, OpenTelemetry

Leadership & Strategic Responsibilities :

- Define enterprise AI reference architecture and roadmap.
- Mentor engineers and ML teams on best practices for agentic AI design.
- Lead build vs buy decisions for AI platforms and tools.
- Establish AI cost governance and FinOps framework.
- Drive cross-functional alignment between business, data, and engineering teams.

Success Metrics (First 6 - 12 Months) :

- Production deployment of at least one enterprise-grade multi-agent system.
- Documented enterprise AI reference architecture and governance model.
- Operational RAG and evaluation framework with measurable performance benchmarks.
- Scaled AI use cases across multiple business domains.
- Optimized AI cost-to-value ratio with clear ROI metrics.

📌 Ingenious Insights - Agentic AI Solution Architect (India)
🏢 Axtria
📍 India