AI Software Engineer - Platform

We are looking for an AI focused Platform Engineer, to join our growing Platform Engineering team, who can drive adoption, enhancement, standardization of agentic AI platforms across the business. This unique position entails designing, building and maintaining common platform oriented solutions for AI enablement as well as executing agentic AI projects for Core Technology. Key Responsibilities: Develop tools and platforms that leverage LLMs, code generation, and intelligent agents to streamline code delivery, testing, and deployment. Collaborate with DevOps, SRE, and software engineering teams to embed AI capabilities into CI/CD pipelines, developer tooling, and infrastructure automation. Champion AI engineering best practices, stay current with emerging trends, and foster a culture of innovation and high standards. Build strong relationships with our applied AI group, platform teams and development community to identify opportunities for AI-enhanced software delivery. Stay up-to-date

with SWE AI trends and pilot AI solutions for software engineering, generative and agentic technologies and issue best practices to the tech teams. Drive AI projects across our Core Technology group, focused on automating processes and delivering AI agents to accelerate capacity and delivery. To be considered a good fit, you must have: 5-7+ years in software engineering, platform engineering, or AI/ML engineering, with a focus on automation, infrastructure as code, or developer productivity. Bachelor's degree in engineering, computer science, information systems, or equivalent experience. Software engineering with Python and one other object-oriented programming language (e.g. C#, Java, C++, GoLang) Deep expertise with AI agent SDKs, frameworks - such as: OpenAI agents SDK, Claude agents SDK, Langchain. Proven experience building and deploying AI/ML solutions in production environments. Expertise in CI/CD design, infrastructure as code, and distributed systems (especially Kubernetes). Experience architecting and implementing testable, scalable, and reliable software and infrastructure solutions. Deep expertise with containers and Kubernetes, including application management and orchestration. Experience working with configuration/infrastructure as code (e.g., Terraform, Kubernetes Operators). Experience working with and maintaining observability solutions. Experience working with both cloud (AWS preferred) and on-premises hosting platforms.