Senior Cloud Architect, ML/AI
United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 4+ years
- Required Skills
- AWSPyTorchTensorflowAWS LambdaMLOps
Requirements
- 4+ years of experience architecting and deploying cloud-based AI/ML solutions in production environments
- Strong expertise in AWS
- Hands-on experience with Amazon Bedrock and SageMaker
- Experience with model training, fine-tuning, deployment, and evaluation of LLMs and generative AI systems
- Strong knowledge of distributed systems, data pipelines, and cloud-native architectures
- Experience building end-to-end ML workflows using S3, Glue, Lambda, Step Functions, and EKS
- Understanding of MLOps practices, including CI/CD for AI systems, monitoring, governance, and model lifecycle management
- Familiarity with frameworks such as TensorFlow or PyTorch
- Experience with data engineering tools
- Strong communication skills
- Consultative mindset and ability to influence technical and non-technical stakeholders
- Experience working in multi-cloud environments and collaborating across sales, product, and engineering teams is highly valued
Responsibilities
- Lead the design, architecture, and implementation of production-grade ML and GenAI solutions on AWS across full data, training, inference, and integration pipelines.
- Translate complex business requirements into scalable, secure, and cost-optimized cloud architectures aligned with customer objectives.
- Serve as a technical advisor across customer engagements, from proof-of-value through production deployment and optimization.
- Design and promote reusable AI/ML architectural patterns, turning field learnings into scalable ‘gravel road’ solutions.
- Partner with sales, customer success, and engineering teams to support adoption, expansion, and successful delivery outcomes.
- Drive AI/ML solution quality through best practices in observability, reliability, security, and operational excellence.
- Contribute to product evolution by sharing insights from customer implementations and influencing roadmap priorities.
- Support both pre-sales (field engineering) and post-sales (delivery) motions depending on business needs.
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