- GenAI Solutions Architect-AWS
Job Title: Generative AI Solutions Architect for AWS Business Enablement Strategy
Role Summary: As the Generative AI Solutions Architect, He/She will be the catalyst for embedding artificial intelligence into the fabric of our business. Mission is to identify, design, and implement high-impact solutions using the AWS AI/ML stack, primarily focusing on Amazon Bedrock and Amazon Q. This role is not just about technology; it's about translating complex business challenges into production-ready, intelligent applications that create new value and a competitive edge.
Key Responsibilities:
- Business Partnership: Collaborate directly with business leaders in Marketing, Customer Service, R&D, and Operations to identify and prioritize use cases for Generative AI.
- Solution Design & Prototyping: Architect end-to-end AI solutions on AWS and rapidly build Proofs of Concept (PoCs) using Amazon Bedrock to demonstrate feasibility and business value.
- Technical Leadership: Act as the company's subject matter expert on foundation models, prompt engineering, Retrieval Augmented Generation (RAG), and fine-tuning techniques within the AWS ecosystem.
- Implementation & Integration: Lead the technical development and integration of AI models into new and existing business applications, using services like AWS Lambda, API Gateway, and Step Functions.
- Champion Responsible AI: Establish and promote best practices for developing and deploying AI that is secure, fair, transparent, and compliant with industry regulations.
Required Qualifications:
- Proven track record of technical leadership with 12+ years in the technology industry, demonstrating the ability to architect and deliver complex, large-scale solutions from concept to production.
- 6+ years of experience in a solutions architecture or software engineering role with a deep, hands-on focus on the AWS ecosystem.
- Proven experience building solutions with Amazon Bedrock, including model evaluation, RAG patterns with Amazon Kendra or OpenSearch, and an understanding of fine-tuning.
- Strong programming proficiency in Python and deep familiarity with the AWS SDK (Boto3) for interacting with AWS services.
- Architectural knowledge of building secure and scalable applications using core AWS services (e.g., IAM, VPC, S3, Lambda, API Gateway).
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
Preferred Qualifications:
- AWS Certified Solutions Architect - Professional or AWS Certified Machine Learning - Specialty.
- Experience with the broader Amazon SageMaker suite for custom model training and MLOps.
- Familiarity with other ML frameworks such as TensorFlow or PyTorch.
- Experience deploying AI solutions in a regulated industry
