GenAI Solutions Architect

Everest DX – We are a Digital Platform Services company, headquartered in Stamford. Our Platform/Solution includes Orchestration, Intelligent operations with BOTs’, AI-powered analytics for Enterprise IT. Our vision is to enable Digital Transformation for enterprises to deliver seamless customer experience, business efficiency and actionable insights through an integrated set of futuristic digital technologies. Digital Transformation Services - Specialized in Design, Build, Develop, Integrate, and Manage cloud solutions and modernize Data centers, build a Cloud-native application and migrate existing applications into secure, multi-cloud environments to support digital transformation. Our Digital Platform Services enable organizations to reduce IT resource requirements and improve productivity, in addition to lowering costs and speeding digital transformation. Digital Platform - Cloud Intelligent Management (CiM) - An Autonomous Hybrid Cloud Management Platform that works across multi-cloud environments. helps enterprise Digital Transformation get most out of the cloud strategy while reducing Cost, Risk and Speed. GenAI Solution Architect (AWS & Azure) Job Type : Full Time Experience : 10+ years (including 3+ years in AI/ML or GenAI architecture) Notice Period - Immediate to 15 days joiners are highly preferred Architect end-to-end Generative AI solutions on AWS and Azure. AWS Bedrock, SageMaker, and Comprehend. Azure OpenAI Service, Azure Machine Learning, and Cognitive Search. Build Retrieval-Augmented Generation (RAG) pipelines integrating vector databases (e.g., Amazon OpenSearch, Pinecone, Azure Cosmos DB + embeddings). Cloud & Infrastructure Architecture Define scalable, secure infrastructure on AWS and Azure: Storage & Data: S3, DynamoDB, Azure Blob, Cosmos DB, Synapse. Networking & Security: VPC, Private Link, IAM, Key Vault, KMS, Defender for Cloud. Leverage API Gateway / Azure API Management for secure AI API deployment. AI/ML Lifecycle & MLOps Architect AI pipelines across training, tuning, and inference stages. Integrate CI/CD for AI workflows using GitHub Actions / Azure DevOps Pipelines. Design monitoring and governance for LLM outputs, model drift, and data quality. Apply Responsible AI principles—bias detection, interpretability, and data privacy. Secure data and models using AWS KMS, Azure Key Vault, and Private Endpoints. Enforce RBAC and least privilege across all AI service components. Partner with Product Owners and Data Leaders to identify GenAI business use cases. Collaborate with developers, data scientists, and cloud engineers for delivery. 5+ years as a Cloud Architect or AI/ML Solution Architect. AWS AI/ML Stack: Bedrock, SageMaker, Comprehend, Rekognition, Lambda. Azure AI Stack: Azure OpenAI, Azure Machine Learning, Cognitive Search, Synapse, Form Recognizer. Strong hands-on in Python and AI orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel). Cloud & DevOps Skills Experience with Terraform, CloudFormation, or Bicep. Proficiency in Docker, Kubernetes (EKS/AKS), and serverless design patterns. Deep understanding of cloud-native identity, encryption, and compliance frameworks. Experience implementing AI guardrails and output moderation workflows. Ability to translate complex AI architectures into business value propositions. Thought leadership in cloud-native AI adoption and digital transformation. AWS Certified Solutions Architect – Professional Microsoft Certified: Azure Solutions Architect Expert Microsoft Certified: Azure AI Engineer Associate AI Generative AI Certification (nice-to-have) Nice-to-Have Experience Designing multi-cloud AI pipelines across AWS and Azure. Using LangGraph, CrewAI, or Dust for AI agent orchestration. Integration of Power BI, Power Platform, or AWS QuickSight for AI analytics. Successful design and deployment of scalable GenAI architectures across AWS & Azure. Reduction in model deployment and iteration times. Improved model performance, governance, and cost efficiency.