Ai Cloud Solution Architect

**About the project**: Join Neurons Lab as an **AI Cloud Solution Architect & Engineer** - a unique hybrid role combining strategic solution design with hands-on engineering execution. You'll bridge the gap between client requirements and technical implementation, designing AI/ML architectures and then building them yourself using modern cloud infrastructure practices. **Our Focus**: We specialize in serving **Banking, Financial Services, and Insurance (BFSI)** enterprise customers with stringent compliance, security, and regulatory requirements. You'll work on mission-critical AI/ML systems where security architecture, data governance, and regulatory compliance are paramount. This role is perfect for technical professionals who love both the "what" and the "how" - architecting elegant solutions AND rolling up their sleeves to code, deploy, and optimize them. You'll work across multiple AI consulting engagements, from Generative AI workshops to enterprise ML platform development, all while maintaining the highest standards of security and compliance required by financial institutions. **Duration**: Part-time long-term engagement with project-based allocations **Reporting**: Direct report to Head of Cloud **Objective**: Deliver end-to-end AI cloud solutions by combining architectural excellence with hands-on engineering capabilities: - ** Architecture & Design**: Gather requirements, design cloud architectures, calculate ROI, and create technical proposals for AI/ML solutions - ** Engineering Excellence**: Build production-grade infrastructure using IaC, develop APIs and prototypes, implement CI/CD pipelines, and manage AI workload operations - ** Client Success**: Transform business requirements into working solutions that are secure, scalable, cost-effective, and aligned with AWS best practices - ** Knowledge Transfer**: Create reusable artifacts, comprehensive documentation, and architectural patterns that accelerate future project delivery **KPI**: **Architecture & Pre-Sales**: - Design and document 3+ solution architectures per month with comprehensive diagrams and specifications - Achieve 80%+ client acceptance rate on proposed architectures and estimates - Deliver ROI calculations and cost models within 2 business days of request **Engineering Delivery**: - Deploy infrastructure through IaC (AWS CDK/Terraform) with zero manual configuration - Create at least 3 reusable IaC components or architectural patterns per quarter - Implement CI/CD pipelines for all projects with automated testing and deployment - Maintain 95%+ uptime for production AI/ML inference endpoints - Document architecture and implementation details weekly for knowledge sharing **Quality & Best Practices**: - Ensure all solutions pass AWS Well-Architected Review standards - Deliver comprehensive documentation within 1 week of architecture completion - Create simplified UIs/demos for PoC validation and client presentations **Areas of Responsibility**: **Solution Architecture (40%)**: **Requirements & Design**: - Elicit and document business and technical requirements from clients - Design end-to-end cloud architectures for AI/ML solutions (training, inference, data pipelines) - Create architecture diagrams, technical specifications, and implementation roadmaps - Evaluate technology options and recommend optimal AWS services for specific use cases **Business Analysis**: - Calculate ROI, TCO, and cost-benefit analysis for proposed solutions - Estimate project scope, timelines, team composition, and resource requirements - Participate in presales activities: technical presentations, demos, and proposal support - Collaborate with sales team on SOW creation and customer workshops **Strategic Planning**: - Design for scalability, security, compliance, and cost optimization from day one - Create reusable architectural patterns and reference architectures - Stay current with AWS AI/ML services and emerging cloud technologies **Cloud Engineering & AI Infrastructure (60%)**: **Infrastructure as Code Development**: - Build and maintain cloud infrastructure using **AWS CDK** (primary) and **Terraform** - Develop reusable IaC components and modules for common patterns - Implement infrastructure for AI/ML workloads: GPU clusters, model serving, data lakes - Manage compute resources: EC2, ECS, EKS, Lambda, SageMaker compute instances **Application Development**: - Create prototype interfaces using Streamlit, React, or similar frameworks - Build and integrate RESTful APIs for AI model serving and data access - Implement authentication, authorization, and API security best practices **AI/ML Operations (MLOps)**: - Deploy and manage AI/ML model serving infrastructure (SageMaker endpoints, containerized models) - Build ML pipelines: data ingestion, preprocessing, training automation, model deployment - Implement model versioning, experiment tracking, and A/B testing frameworks - Manage GPU resource allocation, training job scheduli