Description:
1. Solution Design & Architecture:
Lead architecture, Design, and implementation of AWS solutions:
- Act as AWS Subject Matter Expert (SME) responsible for designing enterprise-grade, scalable, secure, and cost-optimized architectures using AWS services such as EC2, Auto Scaling, ALB/NLB, VPC, Transit Gateway, S3, EFS, FSx, RDS, Aurora, DynamoDB, ElastiCache, Lambda, ECS, EKS, Step Functions. Provide L3/L4 architectural guidance to delivery teams.
DevOps-enabled architectures:
- Design DevOps-first architectures using AWS CodePipeline, CodeBuild, CodeDeploy, GitHub/GitLab, Terraform, AWS CloudFormation, CDK, and CI/CD automation. Define monitoring and observability.
Translate business requirements:
- Lead technical discovery and requirement analysis, converting business and non-functional requirements into solution architectures, HLDs, LLDs, migration roadmaps, and implementation plans aligned to AWS Well- Architected Framework.
Select optimal AWS services:
- Perform service selection and trade-off analysis across compute, storage, databases, networking, security, analytics, and GenAI services, ensuring cost optimization (AWS Cost Explorer, Budgets, Savings Plans), performance, and scalability.
2. Customer Engagement & Technical Leadership:
Go-to technical advisor:
- Act as trusted AWS & GenAI technical advisor for customers, providing architecture governance, design reviews, and escalation support. Represent the company in CXO-level technical discussions.
Thought Leadership:
- Provide guidance on cloud modernization, migration, DevOps, security, DR, cost optimization, and GenAI adoption using AWS best practices.
3. Pre-sales & Delivery Ownership (Mandatory):
Pre-sales solutioning:
- Own end-to-end presales solutioning including requirement discovery, architecture definition, effort estimation, BOM creation, pricing inputs, and proposal responses. Confidently articulate solutions to customers, AWS OEM teams, and internal stakeholders.
4. GenAI & AI/ML Expertise (Mandatory):
GenAI & AI/M:
- Lead GenAI presales solutioning and architecture using Amazon Bedrock (Claude, Titan, Llama), SageMaker, Amazon Q, OpenSearch, and vector databases. Design RAG-based architectures, prompt engineering strategies, data pipelines, and secure AI workloads.
- Advise customers on GenAI use cases such as chatbots, knowledge assistants, document processing, code assistants, AIOps, and enterprise automation. Ensure data privacy, security, and responsible AI using AWS- native controls.
5. AWS OEM Engagement:
AWS partner engagement:
- Act as primary technical interface with AWS, including Partner Development Managers (PDMs), AWS Solution Architects, and Service teams.
Competencies & programs:
- Support AWS competency programs (Migration, DevOps, GenAI), partner validations, and solution reviews. Stay current with AWS service launches and incentives.
6. Best Practices & Enablement:
Best practices:
- Define and evangelize AWS Well-Architected best practices across Security, Reliability, Performance, Cost Optimization, Sustainability, and Operational Excellence pillars.
Mentorship:
- Mentor architects and engineers, providing technical reviews, design feedback, and supporting certification and capability building initiatives.
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