Senior Cloud Consultant AI Solutions Focus

• Role: Senior Cloud Consultant - AI Solutions Focus
• Primary Skill: Amazon Web Services (AWS) Cloud Computing
• Experience Required: 8-10 years
• Focus Areas:
• AWS Cloud Architecture
• Azure Cloud
• Artificial Intelligence (AI)
• Generative AI
• Machine Learning
• Large Language Models (LLMs)
• Cloud-Native Solutions
• Cloud Modernization
• DevOps & Automation
• AI Governance & Security

Role Overview

• Lead the design, implementation, and optimization of modern cloud-based applications.
• Serve as the AI and Cloud champion within the consulting team.
• Drive strategy, architecture, and delivery of intelligent applications using:
• Generative AI
• Machine Learning
• Large Language Models (LLMs)
• Cloud-native services
• Design scalable, secure, resilient, and innovative AI-driven solutions.
• Work closely with:
• Business stakeholders
• Product teams
• Architects
• Developers
• Engineering teams
• Deliver measurable business value through AI and cloud transformation initiatives.

Cloud Architecture & Solution Design

• Lead the design and implementation of cloud-native applications and enterprise solutions on AWS, Azure, and other cloud platforms.
• Define:
• Scalable cloud architectures
• Secure architectures
• Resilient architectures
• Cost-optimized architectures
• Establish cloud design patterns, best practices, and governance standards.
• Evaluate and recommend cloud services, frameworks, and technologies based on business requirements.
• Collaborate with development teams to ensure successful solution delivery.
• Conduct architecture reviews.
• Provide technical leadership across multiple projects.
• Design solutions across:
• Public cloud
• Private cloud
• Hybrid cloud
• Multi-cloud environments

AI Enablement & Innovation

• Identify opportunities to leverage:
• Artificial Intelligence
• Generative AI
• Machine Learning
• Intelligent Automation
• Design and implement AI-enabled solutions using:
• Amazon Bedrock
• Amazon SageMaker
• AWS AI Services
• Azure OpenAI
• Open-source LLM frameworks
• Develop:
• AI use cases
• Proofs of Concept (POCs)
• Production-ready AI solutions
• Partner with stakeholders to assess AI feasibility, business value, and implementation strategies.
• Define architecture patterns for:
• Retrieval-Augmented Generation (RAG)
• AI Agents
• Model orchestration
• Enterprise search
• Promote responsible AI adoption.
• Establish AI governance, security, compliance, and ethical AI practices.
• Define AI model lifecycle management and risk management processes.

Cloud Consulting & Stakeholder Engagement

• Engage with business and technology stakeholders to understand strategic objectives.
• Assess existing IT landscapes and identify cloud adoption and modernization opportunities.
• Develop:
• Cloud strategies
• AI roadmaps
• Cloud modernization roadmaps
• Transformation strategies
• Conduct:
• Cloud readiness assessments
• Application discovery
• Infrastructure discovery
• Dependency analysis
• Workload classification
• Migration planning
• Facilitate:
• Workshops
• Architecture reviews
• Technical discovery sessions
• Serve as a trusted advisor for cloud modernization and AI transformation.
• Create business cases and value realization strategies for AI investments.
• Recommend cloud migration, optimization, and modernization opportunities.
• Recommend appropriate:
• Cloud services
• Migration patterns
• Deployment models
• Build-versus-buy approaches

Cloud Migration & Modernization

• Define cloud adoption strategies and phased transformation roadmaps.
• Design cloud landing zones and target operating models.
• Lead or support:
• Rehosting
• Replatforming
• Refactoring
• Containerization
• Data migration
• Cloud-native modernization
• Support enterprise application and infrastructure migration initiatives.
• Coordinate application migration activities across technical teams.
• Facilitate:
• Testing
• Cutover
• Production readiness
• Knowledge transfer
• Change management
• Operational handover
• Post-migration optimization

Platform Engineering & Automation

• Design and implement Infrastructure as Code (IaC) solutions using:
• Terraform
• AWS CDK
• CloudFormation
• Build automated deployment pipelines and DevOps workflows.
• Implement CI/CD pipelines across cloud environments.
• Automate:
• Infrastructure provisioning
• Monitoring
• Security controls
• Compliance controls
• Operational processes
• Support containerized and serverless workloads using:
• Kubernetes
• Amazon ECS
• Amazon EKS
• AWS Lambda
• Azure Container Apps
• Establish configuration management and automated operational practices.

Security, Governance & Compliance

• Ensure cloud and AI solutions comply with organizational security policies and regulatory requirements.
• Implement:
• Identity and Access Management
• Encryption
• Security monitoring
• Observability
• Access controls
• Define AI governance frameworks.
• Establish model lifecycle management processes.
• Implement AI risk management practices.
• Conduct architecture risk assessments.
• Develop remediation plans.
• Define requirements for:
• IAM
• Networking
• Encryption
• Backup
• Disaster Recovery
• Monitoring
• Logging
• Compliance
• Operational resilience

Operational Excellence

• Monitor cloud solution:
• Performance
• Reliability
• Availability
• Cost efficiency
• Establish observability standards using:
• CloudWatch
• Grafana
• Datadog
• OpenTelemetry
• Support production incidents.
• Lead Root Cause Analysis (RCA) activities.
• Drive continuous improvement focused on:
• Scalability
• Reliability
• Operational efficiency
• Automation

Cloud Cost Management / FinOps

• Support cloud cost management initiatives.
• Define and implement:
• Resource tagging
• Budgeting
• Forecasting
• Rightsizing
• Reservations
• Chargeback
• Cost optimization
• Design cost-efficient cloud architectures.
• Monitor cloud resource utilization and spending., AI / Machine Learning Skills
• Experience implementing enterprise AI and Generative AI solutions.
• Knowledge of:
• Amazon Bedrock
• Amazon SageMaker
• Azure OpenAI
• OpenAI APIs
• LangChain
• LlamaIndex
• Vector Databases
• Semantic Search
• RAG Architectures
• AI Agents
• Understanding of:
• Prompt engineering
• Model evaluation
• AI lifecycle management
• Model governance
• AI compliance
• Familiarity with LLMs such as:
• GPT
• Claude
• Gemini
• Llama
• Experience with Agentic AI frameworks and autonomous workflow orchestration.

Application Development Skills

• Experience supporting cloud-based applications and APIs.
• Proficiency in:
• Python
• Node.js
• Experience building and integrating:
• REST APIs
• Microservices
• Understanding of:
• Event-driven architectures
• Serverless architectures

DevOps & Automation Skills

• Terraform
• AWS CDK
• CloudFormation
• GitHub Actions
• Jenkins
• Azure DevOps
• CI/CD
• Docker
• Kubernetes
• Amazon EKS
• Amazon ECS
• Cloud automation
• Infrastructure as Code
• Configuration management
• Monitoring and observability, Project & Team Leadership
• Coordinate onsite and offshore teams.
• Manage:
• Project milestones
• Dependencies
• Risks
• Issues
• Stakeholder expectations
• Provide clear executive-level status reporting.
• Collaborate with:
• Architects
• Developers
• Infrastructure teams
• Security teams
• Data engineers
• DevOps engineers
• Product owners
• Service providers

https://job.goodword.io/JobLanding/JobId=98a87b9e-c5b0-4ed6-b13d-ace46cd50b63?trafficsourceid=0 external

• Strong expertise in AWS Cloud Services, including:
• EC2
• S3
• EKS
• ECS
• Lambda
• RDS
• DynamoDB
• API Gateway
• VPC
• IAM
• CloudWatch
• Enterprise AWS architecture and migration experience.
• Experience with AWS security, networking, IAM, and cloud-native services.

Azure Skills

• Experience with Microsoft Azure cloud services.
• Experience with:
• Azure OpenAI
• Azure Container Apps
• Ability to design solutions across multi-cloud environments., * Bachelor’s degree in:
• Computer Science
• Engineering
• Information Technology
• Related field
• 8+ years of experience in:
• Cloud Consulting
• Cloud Architecture
• Cloud Engineering
• 3+ years of experience delivering:
• AI solutions
• Machine Learning solutions
• Generative AI solutions
• Proven experience designing and implementing enterprise-scale cloud solutions.
• Strong stakeholder management and consulting skills.
• Excellent:
• Communication
• Presentation
• Problem-solving
• Technical leadership
• Experience leading cross-functional technical initiatives.
• Experience mentoring engineering teams., * AWS Solutions Architect Professional certification.
• AWS Machine Learning Specialty certification.
• Microsoft Azure AI Engineer certification.
• Experience building:
• AI-enabled SaaS platforms
• Enterprise AI applications
• Experience with Agentic AI frameworks.
• Experience with autonomous workflow orchestration.
• Knowledge of:
• Data governance
• Model governance
• AI compliance frameworks