We are seeking an experienced AWS Cloud & AI Platform Engineer II to design, build, and support secure, scalable, and governed AI/GenAI platform solutions within an enterprise environment.
The ideal candidate will have strong hands-on AWS cloud and platform engineering experience, combined with practical expertise in Generative AI, AI/ML enablement, Infrastructure as Code, and enterprise AI governance.
Key Responsibilities:
- Design, develop, and support scalable AWS-based AI/GenAI platforms.
- Build reusable AI enablement frameworks, platform services, and reference architectures.
- Provision and automate AWS infrastructure using Terraform and/or CloudFormation.
- Work hands-on with Amazon Bedrock, SageMaker, Lambda, S3, API Gateway, IAM, and CloudWatch.
- Implement GenAI solutions using RAG, prompt engineering, model orchestration, and agentic AI patterns.
- Integrate enterprise data sources with AI/ML platforms.
- Develop and maintain CI/CD pipelines and automation using Python and DevOps tools.
- Implement AI governance, security controls, guardrails, monitoring, and observability.
- Support AI/ML proof of concepts, experimentation, and production deployments.
- Collaborate with engineering, security, infrastructure, risk, and data teams to ensure enterprise readiness.
Required Qualifications:
- 9+ years of relevant experience in cloud engineering, platform engineering, AI/ML enablement, or enterprise technology.
- Strong hands-on experience with AWS cloud services and platform architecture.
- Practical experience with Amazon Bedrock and/or SageMaker.
- Proficiency in Python programming and scripting.
- Experience with Terraform and/or CloudFormation.
- Knowledge of CI/CD tools such as Jenkins and GitHub.
- Hands-on experience with Generative AI, RAG, and prompt engineering.
- Familiarity with LangChain and/or LlamaIndex.
- Experience with model orchestration, evaluation frameworks, MCP, vector databases, and agentic AI.
- Strong understanding of enterprise AI security, governance, access management, risk management, and compliance.
- Experience building reusable platform frameworks, guardrails, and reference architectures.
Preferred Qualifications:
- Experience with AWS Lex, SQL, and API integrations.
- Knowledge of model lifecycle management and AI/ML observability.
- Experience supporting AI initiatives in regulated enterprise environments.
- Banking or financial services industry experience.
