Role Summary
Avahi is seeking an experienced AI/ML Solutions Architect to join our passionate team. This role combines deep technical expertise with business acumen to craft scalable, resilient, and innovative AI/ML architectures. You will be a trusted advisor to customers, solving complex challenges and guiding them through their AI/ML adoption journey.
As part of the sales organization, you'll collaborate with customers, internal teams, and AWS partners to design and implement cutting-edge solutions while advocating for customer needs and driving best practices. You will also play a pivotal role in enabling field engagement, producing thought leadership content, and contributing to Avahi's growing reputation in the AI/ML/GenAI space.
Key Responsibilities
Customer Engagement
- Build and maintain strong technical relationships with customers, acting as their trusted advisor for AI/ML adoption.
- Manage the overall technical relationship between Avahi, AWS, and customers, providing recommendations for security, performance, reliability, and cost optimization.
- Educate customers on AI/ML/GenAI best practices and guide them through cloud-native architectural solutions.
Solution Architecture
- Design and deliver scalable, flexible, and resilient AI/ML architectures tailored to customer requirements.
- Guide customers in refactoring applications or building entirely new cloud-native AI/ML systems.
- Leverage AWS services, such as SageMaker and Bedrock, to implement state-of-the-art AI/ML solutions.
Thought Leadership & Content Creation
- Create and share best practices, technical content, and reference architectures (e.g., whitepapers, blogs, workshops).
- Evangelize running AI/ML workloads on AWS through public speaking, workshops, meetups, and conferences.
Internal Advocacy
- Serve as the voice of the customer, capturing feedback to influence Avahi's service offerings and AWS roadmap features.
- Collaborate with internal teams to ensure successful implementation of AI/ML projects.
Enablement & Field Engagement
- Conduct training sessions and workshops for internal teams, customers, and partners to share AI/ML knowledge.
- Drive the development of reusable tools and frameworks to enhance operational excellence.
Required Skills and Qualifications
- Hands-on experience with AWS services, including SageMaker and Bedrock.
- Deep knowledge of AI/ML/GenAI domains (e.g., MLOps, ML training, inference, data engineering, model evaluation, fine-tuning, prompt engineering, responsible AI).
- Strong understanding of infrastructure-as-code (IaC) principles with experience using tools like Terraform or CloudFormation.
- Proven track record of delivering successful AWS migration and modernization projects.
- Experience engaging decision-makers and leading complex projects to drive extensible, cost-optimized solutions.
- Familiarity with the AWS Well-Architected Framework and its application to solution design.
- Excellent problem-solving skills and the ability to troubleshoot complex technical issues.
- Strong communication skills, both written and verbal, with experience influencing technical and business stakeholders.
