AWS Cloud Engineer AI/ML Applications, SageMaker

Summary: The role of AWS Cloud Engineer focuses on developing AI/ML applications using AWS services, particularly SageMaker. Candidates are expected to have extensive experience in software engineering, particularly with Python and GoLang or Node.js, and a strong background in machine learning. The position requires hands-on development of applications and contributions to open-source projects, along with a Ph.D. in a relevant field or patents in AI/ML. The role is remote and classified as outside IR35.

Key Responsibilities:

• 10+ years of proven software engineering experience with a strong focus on Python and GoLang and/or Node.js.
• Demonstrated contributions to open-source AI/ML/Cloud projects, with either merged pull requests or public repos showing real usage (forks, stars, or clones).
• Direct, hands-on development of RAG, semantic search, or LLM-augmented applications, using frameworks and ML tooling like Transformers, PyTorch, TensorFlow, and LangChain not just experimentation in a notebook.
• Ph.D. in AI/ML/Data Science and/or named inventor on pending or granted patents in machine learning or artificial intelligence.
• Deep expertise with AWS services, especially Bedrock, SageMaker, ECS, and Lambda.
• Proven experience fine-tuning large language models, building datasets, and deploying ML models to production.
• Demonstrated success delivering production-ready software with release pipeline integration.
• Policy as Code development (i.e., Terraform Sentinel) to manage and automate cloud policies, ensuring compliance.
• Experience optimizing cost-performance in AI systems (FinOps mindset).
• Awareness of data privacy and compliance best practices (e.g., PII handling, secure model deployment).
• Demonstrated experience with AWS organizations and policy guardrails (SCP, AWS Config).

Key Skills:

• 10+ years of software engineering experience.
• Strong focus on Python and GoLang and/or Node.js.
• Experience with open-source AI/ML/Cloud projects.
• Hands-on development of RAG, semantic search, or LLM-augmented applications.
• Ph.D. in AI/ML/Data Science or patents in machine learning or AI.
• Expertise with AWS services, especially Bedrock, SageMaker, ECS, and Lambda.
• Experience fine-tuning large language models and deploying ML models.
• Experience with Policy as Code development (Terraform Sentinel).
• Cost-performance optimization in AI systems.
• Knowledge of data privacy and compliance best practices.
• Experience with AWS organizations and policy guardrails.

Salary (Rate): undetermined

City: undetermined

Country: USA

Working Arrangements: remote

IR35 Status: outside IR35

Seniority Level: undetermined

Industry: IT