Role Overview:We are seeking a highly skilled Senior Cloud Consultant with a specialization in Artificial Intelligence and Cloud-Native Solutions to lead the design, implementation, and optimization of modern cloud-based applications. This individual will serve as the AI and Cloud champion within the consulting team, helping drive the strategy, architecture, and delivery of intelligent applications powered by Generative AI, Machine Learning, Large Language Models (LLMs), and cloud-native services. The ideal candidate has deep expertise in AWS and experience leveraging AI services across AWS, Azure, and other cloud platforms, working closely with stakeholders to design scalable, secure, and innovative AI-driven solutions that deliver measurable business value. This role combines cloud architecture, AI solutioning, technical leadership, governance, and hands-on implementation to accelerate digital transformation initiatives.
Key Responsibilities:- 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, establishing design patterns, best practices, and governance standards.
- Evaluate and recommend cloud services, frameworks, and technologies aligned with business requirements.
- 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 Amazon Bedrock, Amazon SageMaker, AWS AI Services, Azure OpenAI, and open-source LLM frameworks.
- Develop AI use cases, proof-of-concepts, and production-ready solutions, defining patterns for Retrieval-Augmented Generation (RAG), AI agents, and enterprise search integrations.
- Engage with business and technical stakeholders to understand strategic objectives and translate them into cloud and AI roadmaps.
- Design and implement Infrastructure as Code (IaC) solutions using Terraform, AWS CDK, CloudFormation, or similar tools, and build automated deployment pipelines and DevOps workflows.
- Ensure cloud and AI solutions adhere to organizational security policies and regulatory requirements, implementing identity, access management, encryption, and security monitoring controls.
- Monitor cloud solution performance, reliability, and cost efficiency, establishing observability standards and supporting production incidents.
Required Skills:- Deep expertise in AWS cloud services including EC2, S3, EKS, ECS, Lambda, RDS, DynamoDB, API Gateway, VPC, IAM, and CloudWatch.
- Experience with Azure cloud services and cloud architecture and migration for enterprise workloads.
- Experience implementing AI and Generative AI solutions in enterprise environments.
- Knowledge of Amazon Bedrock, SageMaker, Azure OpenAI, OpenAI APIs, LangChain, LlamaIndex, Vector Databases, Semantic Search, RAG Architectures, and AI Agents.
- Understanding of prompt engineering, model evaluation, AI lifecycle management, and familiarity with LLMs such as GPT, Claude, Gemini, or Llama.
- Proficiency in Python or Node.js, experience building and integrating REST APIs and microservices, and understanding of event-driven and serverless architectures.
- DevOps & Automation: Terraform, CloudFormation, AWS CDK, GitHub Actions, Jenkins, Azure DevOps, 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 Skills:- 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.
