About AllCloud

AllCloud is a leader in amplifying organizations’ cloud potential through AI. With a track record of hundreds of successful migrations and implementations across AWS and Salesforce, AllCloud has developed strategies and solutions that enable businesses of all sizes to remain at the forefront of innovation.

AllCloud is a leader in AI-led professional and managed services. As an AWS Premier and audited managed services Partner, and Salesforce Consulting partner, AllCloud provides comprehensive AI-led cloud journey support, from initial migration to ongoing management through our Engage Managed Services. Our expertise ensures that clients remain aligned with ecosystem best practices while focusing on their core business growth.

AllCloud serves clients across the globe with offices in EMEA and North America. www.allcloud.io

Role Overview

In this customer-facing role, you will work closely with business stakeholders, engineering teams, and cloud architects to define solution architectures, lead technical workshops, and implement secure, scalable, and cost-efficient AI applications on AWS. The ideal candidate combines strong AWS architecture experience with hands-on expertise in Bedrock, Retrieval-Augmented Generation (RAG), AI agents, and cloud-native application design.

Key Responsibilities

• Lead customer discovery sessions, technical workshops, and architecture discussions.
  

• Design secure, scalable, resilient, and cost-optimized AWS cloud solutions.
  

• Architect and implement enterprise Generative AI solutions using Amazon Bedrock and foundation models.
  

• Guide customers through cloud modernization, application migration, and AI adoption initiatives.
  

• Prepare High-Level Designs (HLDs), Low-Level Designs (LLDs), architecture diagrams, Statements of Work (SOWs), and technical proposals.
  

• Define best practices for security, scalability, governance, observability, and operational excellence.
  

• Collaborate with DevOps, FinOps, Data Engineering, AI, and Delivery teams to ensure successful project execution.
  

• Act as a trusted technical advisor throughout the customer engagement lifecycle.
  

• Mentor engineering teams on AWS architecture, cloud-native design patterns, and Generative AI implementation.
  

• Stay current with emerging AWS services, AI technologies, and industry best practices.
  

Requirements

Skills & Qualifications

• 8+ years of experience designing, architecting, and delivering enterprise cloud solutions.
  

• Minimum 2 years of hands-on experience with AWS cloud architecture.
  

• Experience in customer-facing consulting, professional services, or solution architecture roles.
  

• Proven ability to design secure, scalable, highly available, and cost-optimized cloud solutions.
  

• Experience leading technical discussions, architecture reviews, and customer workshops.
  

• Strong expertise in designing and implementing solutions using AWS services, including:
  

• Compute: EC2, Lambda, ECS/Fargate
  

• Networking: VPC, Route 53, API Gateway
  

• Storage & Databases: S3, RDS, DynamoDB
  

• Integration & Orchestration: Step Functions, EventBridge
  

• Security & Identity: IAM, Secrets Manager, KMS
  

• Monitoring & Observability: CloudWatch, AWS X-Ray
  

• Hands-on experience designing and implementing Generative AI solutions using AWS services.
  

• Experience with:
  

• Amazon Bedrock
  

• Foundation Models (Claude, Llama, Titan, etc.)
  

• Prompt Engineering
  

• Model evaluation and optimization
  

• Amazon Bedrock Knowledge Bases
  

• Guardrails for Amazon Bedrock
  

• Experience building intelligent AI agent solutions, including:
  

• Agentic workflows and autonomous task execution
  

• Tool calling and external API integrations
  

• Memory management and multi-step reasoning
  

• Workflow orchestration using AWS services
  

• Designing scalable, reliable, and low-latency AI applications
  

• Experience with:
  

• Infrastructure as Code (Terraform and/or AWS CloudFormation)
  

• CI/CD pipelines (GitHub Actions, Jenkins, Azure DevOps, AWS CodePipeline)
  

• Containerized deployments
  

• Multi-region deployments and release strategies
  

• Strong understanding of:
  

• Cloud monitoring and observability
  

• Performance optimization and troubleshooting
  

• Cost optimization for AWS and Generative AI workloads
  

• Security best practices, IAM policies, encryption, and API key management
  

• Governance, compliance, and data privacy for AI applications
  

• Working knowledge of one or more programming languages:
  

• Python (Preferred)
  

• TypeScript
  

• Java or Node.js
  

• Experience integrating cloud applications with enterprise platforms and APIs.
  

• AWS Certified Solutions Architect – Professional or Associate.
  

• AWS Certified AI Practitioner or Machine Learning Specialty (preferred).
  

• Experience with LangChain, LangGraph, LlamaIndex, CrewAI, or similar AI frameworks.