AWS Cloud Engineer I

Summary: The AWS Cloud Engineer I role is a remote position focused on leveraging AWS services to develop cloud-native solutions and support intelligent automation. Candidates should possess extensive experience in software engineering, particularly with Python, and familiarity with AWS services such as Bedrock and SageMaker. The role involves collaboration with stakeholders to create scalable AI systems and manage the software release lifecycle. Strong communication skills and a solid understanding of machine learning frameworks are essential for success in this position.

Key Responsibilities:

• Create and maintain technical documentation for the team to reference and share with internal customers.
• Hands-on role using AWS (Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, S3).
• Develop cloud-native microservices, APIs, and serverless functions to support intelligent automation and real-time data processing.
• Collaborate with internal stakeholders to understand business goals and translate them into secure, scalable AI systems.
• Responsible for the implementation of AWS cloud services including infrastructure, machine learning, and artificial intelligence platform services.
• Experience with LLM-based applications, including Retrieval-Augmented Generation (RAG) using LangChain and other frameworks.
• Own the software release lifecycle, including CI/CD pipelines, GitHub-based SDLC, and infrastructure as code (Terraform).
• Support the development and evolution of reusable platform components for AI/ML operations.
• Excellent verbal and written communication skills in English.

Key Skills:

• AWS or relevant cloud certifications.
• 7 years of hands-on software engineering experience with a strong focus on Python.
• Experienced with AWS services, especially Bedrock or SageMaker, ECS and Lambda.
• Experience implementing RAG architectures and using frameworks and ML tooling like: Transformers, PyTorch, TensorFlow, and LangChain.
• Familiar with fine-tuning large language models or building datasets and/or deploying ML models to production.
• Demonstrated experience with AWS organizations and policy guardrails (SCP, AWS Config).
• Solid experience implementing RAG architecture and LangChain.
• Demonstrated experience in Infrastructure as Code best practices and experience with building Terraform modules for AWS cloud.
• Strong background in Git-based version control, code reviews, and DevOps workflows.
• Demonstrated success delivering production-ready software with release pipeline integration.
• Policy as Code development (e.g., Terraform Sentinel).
• Experience with Hugging Face, Golang, or Node.js.
• Exposure to FinOps and cloud cost optimization.
• Data science background or experience working with structured/unstructured data.
• Awareness of data privacy and compliance best practices (e.g., PII handling, secure model deployment).

Salary (Rate): undetermined

City: undetermined

Country: USA

Working Arrangements: remote

IR35 Status: outside IR35

Seniority Level: undetermined

Industry: IT