Cloud Solutions Architect – GenAI

ROLEDESCRIPTION:

Job Summary

• Seeking a highly skilled Senior Cloud Consultant specializing in Artificial Intelligence and Cloud-Native Solutions.
• Lead the design implementation and optimization of modern cloud-based and AI-driven applications.
• Serve as the AI and Cloud champion within the consulting team driving strategy architecture governance and delivery.
• Leverage Generative AI Machine Learning LLMs and cloud-native services to deliver scalable and innovative solutions.
• Partner with business stakeholders product teams architects and engineering teams to translate business requirements into secure scalable and cost-effective technical solutions.

Key Responsibilities

Cloud Architecture & Solution Design

• Lead the design and implementation of cloud-native applications and enterprise solutions across AWS Azure and other cloud platforms.
• Design scalable secure resilient highly available and cost-optimized cloud architectures.
• Establish cloud architecture patterns standards best practices and governance frameworks.
• Evaluate and recommend cloud services frameworks and technologies based on business and technical requirements.
• Collaborate with development and engineering teams to ensure successful solution delivery and operational excellence.
• Conduct architecture reviews and provide technical leadership across multiple projects.
• Develop cloud modernization migration and transformation strategies.

AI Machine Learning & Generative AI

• Identify and evaluate opportunities to apply AI Machine Learning Generative AI and intelligent automation to business processes and products.
• Design and implement enterprise AI solutions using:
  • Amazon Bedrock
  • Amazon SageMaker
  • AWS AI Services
  • Azure OpenAI
  • OpenAI APIs
  • Open-source LLM frameworks
• Develop AI proof-of-concepts (POCs) and production-ready enterprise solutions.
• Design and implement RAG (Retrieval-Augmented Generation) architectures.
• Develop solutions involving AI agents model orchestration semantic search and enterprise search.
• Apply prompt engineering model evaluation and LLM lifecycle management practices.
• Work with foundation models such as GPT Claude Gemini Llama and similar models.
• Define and promote responsible AI security governance compliance and ethical AI practices.

Cloud Consulting & Stakeholder Engagement

• Engage with business and technical stakeholders to understand strategic objectives and translate them into cloud and AI roadmaps.
• Lead technical discovery sessions architecture workshops and solution-design discussions.
• Serve as a trusted technical advisor for cloud modernization and AI transformation initiatives.
• Develop business cases and value-realization strategies for AI and cloud investments.
• Provide recommendations for cloud migration modernization optimization and transformation.
• Communicate complex technical concepts effectively to both technical and non-technical stakeholders.

Platform Engineering & Automation

• Design and implement Infrastructure as Code (IaC) solutions using:
  • Terraform
  • AWS CDK
  • CloudFormation
  • Similar IaC technologies
• Design and implement automated CI/CD and DevOps pipelines.
• Automate infrastructure provisioning monitoring security and compliance controls.
• Support containerized and serverless workloads using:
  • Kubernetes
  • Amazon EKS
  • Amazon ECS
  • AWS Lambda
  • Azure Container Apps
• Drive automation and standardization across cloud environments.

Security Governance & Compliance

• Ensure cloud and AI solutions comply with organizational security policies and regulatory requirements.
• Implement IAM identity management encryption security monitoring and access controls.
• Establish AI governance frameworks and model lifecycle management processes.
• Define AI risk management and responsible AI practices.
• Conduct architecture risk assessments and develop remediation strategies.
• Ensure security and compliance are embedded throughout the solution lifecycle.

Operational Excellence

• Monitor cloud applications and infrastructure for performance reliability scalability and cost efficiency.
• Establish cloud-native observability monitoring and logging standards.
• Support production environments and participate in incident management.
• Lead Root Cause Analysis (RCA) and remediation activities.
• Drive continuous improvement across cloud infrastructure applications and AI platforms.

Required Technical Skills

Cloud Platforms

• Strong hands-on expertise in AWS.
• Experience with:
  • EC2
  • S3
  • EKS
  • ECS
  • Lambda
  • RDS
  • DynamoDB
  • API Gateway
  • VPC
  • IAM
  • CloudWatch
• Experience with Microsoft Azure cloud services.
• Strong knowledge of cloud architecture migration modernization and enterprise-scale workloads.

AI & Machine Learning

• Proven experience implementing AI Machine Learning and Generative AI solutions in enterprise environments.
• Strong 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 LLM orchestration and AI lifecycle management.
• Experience working with foundation models such as GPT Claude Gemini and Llama.

Application Development

• Experience supporting and designing cloud-based applications and APIs.
• Proficiency in Python and/or .
• Experience developing and integrating REST APIs and microservices.
• Understanding of event-driven and serverless architectures.

DevOps & Automation

• Hands-on experience with:
  • Terraform
  • AWS CDK
  • CloudFormation
  • Docker
  • Kubernetes
• Experience with CI/CD platforms such as:
  • GitHub Actions
  • Jenkins
  • Azure DevOps
  • Equivalent CI/CD tools
• Experience with monitoring and observability platforms such as:
  • Grafana
  • Datadog
  • OpenTelemetry
  • CloudWatch

Qualifications & Experience

• Bachelors degree in Computer Science Engineering Information Technology or a related field.
• 8 years of experience in cloud consulting cloud architecture or cloud engineering.
• 3 years of hands-on experience delivering AI Machine Learning or Generative AI solutions.
• Proven experience designing and implementing enterprise-scale cloud and AI solutions.
• Strong experience in cloud architecture solution design and technical consulting.
• Excellent stakeholder management and consulting skills.
• Strong communication presentation analytical and problem-solving abilities.
• Experience leading cross-functional technical initiatives.