Senior Cloud Consultant

Job Title:Senior Cloud Consultant
Location: Indianapolis, IN Onsite
Duration: 6 months
Experience:8-10 Years

Role Descriptions:

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. They will work closely with business stakeholders, product teams, architects, and developers 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 the organization's digital transformation initiatives.

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.