Description

 KEY RESPONSIBILITIES

Cloud Architecture & Solution Design · Lead the design and implementation of cloud-native applications and enterprise solutions on AWS, Azure, or other cloud platforms. · Define scalable, secure, resilient, and cost-optimized cloud architectures. · Establish cloud design patterns, best practices, and governance standards. · Evaluate and recommend cloud services, frameworks, and technologies aligned with business requirements. · Collaborate with development teams to ensure successful solution delivery and operational excellence. · Conduct architecture reviews and provide technical leadership across multiple projects. AI Enablement & Innovation · Identify opportunities to leverage Artificial Intelligence, Generative AI, Machine Learning, and intelligent automation across business processes and products. · Design and implement AI-enabled solutions using services such as: o Amazon Bedrock o Amazon SageMaker o AWS AI Services o Azure OpenAI o Open-source LLM frameworks · Develop AI use cases, proof-of-concepts, and production-ready solutions. · Partner with stakeholders to assess feasibility, business value, and implementation strategies for AI initiatives. · Define patterns for Retrieval-Augmented Generation (RAG), AI agents, model orchestration, and enterprise search integrations. · Promote responsible AI adoption, governance, security, 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. · Facilitate workshops, architecture reviews, and technical discovery sessions. · Serve as a trusted advisor on cloud modernization and AI transformation initiatives. · Create business cases and value realization strategies for AI-driven investments. · Provide recommendations on cloud migration, optimization, and modernization opportunities. Platform Engineering & Automation · Design and implement Infrastructure as Code (IaC) solutions using Terraform, AWS CDK, CloudFormation, or similar tools. · Build automated deployment pipelines and DevOps workflows. · Implement CI/CD pipelines across cloud environments. · Drive automation of infrastructure provisioning, monitoring, security, and compliance controls. · Support containerized and serverless workloads using technologies such as Kubernetes, ECS, EKS, Lambda, and Azure Container Apps. Security, Governance & Compliance · Ensure cloud and AI solutions adhere to organizational security policies and regulatory requirements. · Implement identity, access management, encryption, observability, and security monitoring controls. · Define AI governance frameworks, model lifecycle management processes, and risk management practices. · Conduct architecture risk assessments and remediation planning. Operational Excellence · Monitor cloud solution performance, reliability, and cost efficiency. · Establish observability standards using cloud-native monitoring and logging platforms. · Support production incidents and lead root cause analysis activities. · Drive continuous improvement initiatives focused on scalability, reliability, and operational efficiency. REQUIRED TECHNICAL SKILLS Cloud Platforms · Deep expertise in AWS cloud services including: o EC2 o S3 o EKS o ECS o Lambda o RDS o DynamoDB o API Gateway o VPC o IAM o CloudWatch · Experience with Azure cloud services. · Cloud architecture and migration experience for enterprise workloads. Artificial Intelligence & Machine Learning · Experience implementing AI and Generative AI solutions in enterprise environments. · Knowledge of: o Amazon Bedrock o SageMaker o Azure OpenAI o OpenAI APIs o LangChain o LlamaIndex o Vector Databases o Semantic Search o RAG Architectures o AI Agents · Understanding of prompt engineering, model evaluation, and AI lifecycle management. · Familiarity with LLMs such as GPT, Claude, Gemini, Llama, or similar foundation models. Application Development · Experience supporting cloud-based applications and APIs. · Proficiency in Python or Node.js. · Experience building and integrating REST APIs and microservices. · Understanding of event-driven and serverless architectures. DevOps & Automation · Terraform, CloudFormation, or AWS CDK. · GitHub Actions, Jenkins, Azure DevOps, or equivalent CI/CD platforms. · Docker and Kubernetes. · Monitoring and observability solutions including Grafana, Datadog, OpenTelemetry, or CloudWatch. QUALIFICATIONS · Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field. · 8+ years of experience in cloud consulting, cloud architecture, or cloud engineering roles. · 3+ years of experience delivering AI, Machine Learning, or Generative AI solutions. · Proven experience designing and implementing enterprise-scale cloud solutions. · Strong stakeholder management and consulting skills. · Excellent communication, presentation, and problem-solving abilities. · Experience leading cross-functional technical initiatives and mentoring engineering teams. PREFERRED QUALIFICATIONS · AWS Solutions Architect Professional certification. · AWS Machine Learning Specialty certification. · Microsoft Azure AI Engineer certification. · Experience building AI-enabled SaaS platforms and enterprise applications. · Experience with Agentic AI frameworks and autonomous workflow orchestration. · Knowledge of data governance, model governance, and AI compliance frameworks. KEY SUCCESS MEASURES · Successful delivery of scalable, secure, AI-enabled cloud solutions. · Increased adoption of AI technologies across business applications. · Improved operational efficiency through automation and intelligent workflows. · Measurable business outcomes from AI and cloud transformation initiatives. · High stakeholder satisfaction and trusted-advisor relationships. · Establishment of reusable cloud and AI architecture standards across the organization

Key Skills

Education

Any Gradute