Cloud & AI Solutions Architect

Job Title: Cloud & AI Solutions Architect
Experience: 12+ Years
Employment Type: W2

Position Overview

We are seeking a highly experienced Cloud & AI Solutions Architect with 12+ years of experience in designing, architecting, and implementing enterprise-scale cloud and AI solutions. The ideal candidate will possess deep expertise in cloud platforms, artificial intelligence, machine learning, Generative AI, enterprise architecture, and cloud-native technologies.

This role will be responsible for defining cloud and AI strategy, designing scalable architectures, leading digital transformation initiatives, and enabling organizations to leverage AI and cloud technologies to drive innovation and business value.

Key Responsibilities

Cloud Architecture & Strategy

• Design and implement scalable, secure, and highly available cloud architectures across AWS, Azure, and/or Google Cloud Platform.
• Define enterprise cloud adoption strategies, migration roadmaps, and modernization initiatives.
• Lead cloud transformation programs involving application modernization, containerization, and microservices.
• Establish cloud governance, security, compliance, and cost optimization frameworks.
• Architect multi-cloud and hybrid-cloud solutions.

Artificial Intelligence & Generative AI Solutions

• Design enterprise AI and Generative AI platforms leveraging Large Language Models (LLMs).
• Architect Retrieval-Augmented Generation (RAG) solutions for enterprise knowledge management.
• Design AI-powered copilots, chatbots, virtual assistants, and intelligent automation solutions.
• Evaluate and integrate foundation models such as GPT, Claude, Gemini, Llama, and Mistral.
• Develop AI governance, responsible AI, and model monitoring frameworks.
• Lead AI solution deployment and operationalization using LLMOps and MLOps best practices.

Solution Architecture

• Create end-to-end solution architectures integrating cloud services, AI platforms, APIs, data lakes, and enterprise systems.
• Design microservices-based and event-driven architectures.
• Develop architecture standards, reference architectures, and technology roadmaps.
• Collaborate with business and technical stakeholders to align solutions with strategic objectives.

Data & Analytics

• Architect modern data platforms supporting AI and analytics workloads.
• Design data lakes, data warehouses, real-time streaming solutions, and vector search architectures.
• Implement enterprise data governance, security, lineage, and quality frameworks.

Leadership & Stakeholder Management

• Serve as a trusted advisor to business leaders, product teams, and technology executives.
• Lead architecture reviews, technical governance, and solution design workshops.
• Mentor architects, engineers, and development teams.
• Drive innovation by evaluating emerging cloud and AI technologies.

Required Qualifications

Experience

• 12+ years of experience in software engineering, cloud architecture, or enterprise solution architecture.
• 5+ years of experience designing cloud-native solutions.
• 3+ years of experience implementing AI/ML and Generative AI solutions.
• Proven experience delivering large-scale enterprise transformation initiatives.

Technical Skills

Cloud Platforms

Strong experience with one or more:

• Amazon Web Services (AWS)
• Microsoft Azure
• Google Cloud Platform (Google Cloud Platform)

Cloud Services

Experience with:

• Compute Services (EC2, Azure VM, GCE)
• Kubernetes (EKS, AKS, GKE)
• Serverless Computing
• API Management
• Event Streaming
• Cloud Security Services
• Identity & Access Management (IAM)
• Networking & Infrastructure Design

Artificial Intelligence & Generative AI

Hands-on experience with:

• Large Language Models (LLMs)
• Generative AI Applications
• Retrieval-Augmented Generation (RAG)
• Prompt Engineering
• AI Agents & Multi-Agent Systems
• Fine-Tuning and Model Optimization
• Semantic Search
• Knowledge Graphs

AI Frameworks

Experience with:

• LangChain
• LangGraph
• LlamaIndex
• Semantic Kernel
• CrewAI
• AutoGen

Machine Learning

Experience with:

• PyTorch
• TensorFlow
• Scikit-learn
• Hugging Face Transformers
• Model Deployment and Monitoring

Programming Languages

Strong proficiency in:

• Python
• Java
• JavaScript/TypeScript
• SQL

DevOps, MLOps & LLMOps

Experience with:

• CI/CD Pipelines
• GitHub Actions
• Jenkins
• Terraform
• Infrastructure as Code (IaC)
• MLflow
• Kubeflow
• Docker
• Kubernetes

Databases & Data Platforms

Experience with:

• PostgreSQL
• MySQL
• MongoDB
• Redis
• Snowflake
• Databricks
• Delta Lake
• Vector Databases (Pinecone, Weaviate, Milvus, ChromaDB, FAISS)

Architecture Expertise

Strong knowledge of:

• Enterprise Architecture Frameworks (TOGAF preferred)
• Microservices Architecture
• Event-Driven Architecture
• Domain-Driven Design (DDD)
• API-First Design
• Cloud-Native Architecture
• Security Architecture
• Zero Trust Security Model
• High Availability and Disaster Recovery

Preferred Qualifications

• Experience in Financial Services, Banking, Insurance, Healthcare, Retail, or Technology sectors.
• Experience with Responsible AI and AI Governance frameworks.
• Knowledge of cloud security standards and compliance requirements.
• Experience with AI observability and model evaluation platforms.
• Experience integrating AI solutions with enterprise applications such as Salesforce, ServiceNow, SAP, and Workday.
• Experience with Data Mesh and modern data architecture patterns.

Certifications (Preferred)

Cloud Certifications

• AWS Certified Solutions Architect – Professional
• AWS Certified Machine Learning Specialty
• Microsoft Azure Solutions Architect Expert
• Microsoft Azure AI Engineer Associate
• Google Professional Cloud Architect
• Google Professional Machine Learning Engineer

Architecture Certifications

• TOGAF Certified
• Certified Kubernetes Administrator (CKA)

Key Skills Summary

Cloud: AWS, Azure, Google Cloud Platform, Kubernetes, Serverless, Terraform, Cloud Security

AI & GenAI: LLMs, GPT, Claude, Gemini, Llama, RAG, AI Agents, Prompt Engineering, LangChain, LangGraph, LlamaIndex

Data: Databricks, Snowflake, Delta Lake, Data Lakes, Vector Databases

DevOps/MLOps: Docker, Kubernetes, GitHub Actions, Jenkins, MLflow, Kubeflow

Programming: Python, Java, JavaScript, SQL

Architecture: Enterprise Architecture, Microservices, Event-Driven Systems, Cloud-Native Design, Security Architecture