Description:

The position is for a Senior Cloud AI Software Engineer within the Public Cloud Engineering team, focusing on implementing new features and capabilities using modern information technology engineering tools and practices.
The role involves designing, building, and maintaining secure, scalable AI/ML solutions on AWS, with an emphasis on production-grade infrastructure, LLM fine-tuning, and Retrieval-Augmented Generation (RAG) systems.
Responsibilities include hands-on implementation of AWS cloud services, engineering and deploying end-to-end AI/ML services, and developing cloud-native microservices, APIs, and serverless functions.
The engineer will collaborate with internal stakeholders to align business goals with secure, scalable AI systems and will own the software release lifecycle, including CI/CD pipelines and infrastructure as code.
The role requires creating and maintaining technical documentation for team reference and internal customer sharing.

Requirements:

Candidates must have 7+ years of hands-on software engineering experience, with a strong focus on Python and GoLang.
Deep expertise with AWS services, particularly Bedrock, SageMaker, ECS, and Lambda, is required.
Proven experience in fine-tuning large language models, building datasets, and deploying ML models to production is essential.
Demonstrated experience with AWS organizations and policy guardrails, including SCP and AWS Config, is necessary.
Solid experience in implementing RAG architectures and using frameworks and ML tooling such as Transformers, PyTorch, TensorFlow, and LangChain is required.
Candidates should have experience in Infrastructure as Code best practices and building Terraform modules for AWS cloud.
A strong background in Git-based version control, code reviews, and DevOps workflows is necessary.
Excellent verbal and written communication skills in English are required.
AWS or relevant cloud certifications are a plus, as well as experience with Policy as Code development, Hugging Face, Node.js, and exposure to FinOps and cloud cost optimization.
A data science background or experience with structured/unstructured data and awareness of data privacy and compliance best practices is also advantageous.

The position offers the opportunity to work remotely on a contracted basis.
Engineers will be part of a high-impact team that values curiosity, collaboration, and tackling challenging problems with modern technologies.
The role provides a chance to work on cutting-edge cloud-native AI solutions in a real-world enterprise setting.
Employees will have the opportunity to contribute to the development and evolution of reusable platform components for AI/ML operations.
The position encourages continuous learning and professional growth in a dynamic and innovative environment.