Senior Cloud & AI Platform Engineer

We are currently supporting our international client from the banking sector in hiring a Senior Cloud & AI Platform Engineer to join a growing AI platform team.

The role focuses on building scalable, production-grade AI and cloud infrastructure supporting predictive and generative AI solutions in an enterprise environment.

Main responsibilities:

• You won’t just provision resources; you will form opinions and design reusable integration patterns that standardize how we do AI. You will balance the freedom developers need with the governance a bank requires.
• You will engineer the infrastructure supporting our most advanced capabilities, utilizing AWS SageMaker, Bedrock, and AgentCore to power LLM and predictive workflows.
• You will move beyond “proof of concept” code. You are responsible for designing production-quality services, CI/CD pipelines, and infrastructure that stands up to the rigors of a highly regulated industry.
• As a senior member of the team, you will mentor engineers, collaborate closely with data scientists and DevOps, and help grow a new, engineering-driven team culture.

Profile:

This is the right role for you if you:

• Proven, hands-on experience designing and building production-quality applications or services on AWS and other cloud providers. You understand the difference between “it works on my machine” and “it works at scale.”
• Treat infrastructure as software. You are comfortable writing Python and managing complex environments with Terraform
• Have the soft skills to collaborate across functions. You can speak “Data Science” to the modelers and “Security” to the CISOs, ensuring our platform is both usable and compliant
• Have a genuine interest in the evolving landscape of AI (LLMs, Agentic workflows) and know how to pragmatically apply new concepts to solve real business problems

Background and skills:

• BSc or MSc in Computer Science, Computer Engineering, Engineering Physics, relevant technical field, or equivalent practical experience
• 10+ years of experience in testing, maintaining, launching AI/ML products, working with MLOps best practices and DevOps environment (CI/CD pipelines, Docker, container orchestration)
• Experience in training, evaluation, fine-tuning and deployment of predictive models; including feature selection, hyper-parameter tuning, error analysis and data visualization
• Vast experience and track record of successfully working with the following tech stacks:

o Infrastructure as Code: Terraform (Essential), Python
o AI/ML Platform: Amazon SageMaker, AWS Bedrock, AgentCore
o Data Platform: S3, AWS Glue, Lake Formation
o Languages: Python (Primary), SQL

• Experience working with public cloud providers (AWS, Azure or GCP), especially their serverless, ML (e.g., AWS SageMaker), or data storage services as well as Infrastructure as Code (IaC)
• Skilled at transforming complex ideas into clear, engaging explanations—whether you’re presenting to a technical team or breaking things down for non-experts

Nice to have:

• Professional experience working in regulated industries such as banking, insurance, government, or similar sectors.