AI/ML Solution Architect in Noida, India

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 https://jobeax.com/link/hsoXmLiEZkO29En7 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 https://jobeax.com/link/BsfCGg64DtWZFq1U 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.- Preferred Qualifications :- AWS Certified Solutions Architect - Professional.- Experience deploying production-grade agentic systems.- Background in regulated industries such as Pharma, Healthcare, or Financial Services.- Experience implementing AI governance and compliance https://jobeax.com/link/fYkUIOy2IXm0AvFu 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: 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 https://jobeax.com/link/7CpQ1UBuqJUS25b5 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. (