Software Engineer III – AI/ML Platform Reliability

Overview

In this role you will strengthen the reliability and scalability of AI/ML platforms within a global financial services tech organization. You will collaborate across teams to deliver trusted, production-grade systems and tooling that support large-scale AI capabilities. You’ll own reliability requirements, contribute to observability and security, and tackle complex production problems in a fast-growing environment. This opportunity lets you shape how the firm operationalizes AI with a focus on resilience and secure delivery.

Responsibilities

• Enhance reliability and scalability of AI/ML platforms and applications to meet growing demand
• Own non-functional requirements and develop tooling for observability, security, resilience, and operations excellence
• Build and maintain scalable infrastructure for deployment and operation of large-scale AI platforms and apps
• Foster cross-functional relationships and deliver solutions to user problems
• Participate in on-call rotations, troubleshoot production issues, and take ownership of problems
• Develop and review secure, high-quality production code and assist peers with debugging
• Automate remediation of recurring issues to improve system stability
• Leverage enterprise AI-assisted development tools to improve code quality, delivery speed, and productivity while ensuring secure coding and peer review

Key requirements

• Formal training or certification in software engineering concepts
• Hands-on experience delivering system design, application development, testing, and operational stability
• Advanced proficiency in Python
• Experience across the Software Development Life Cycle
• Experience with infrastructure-as-code and cloud-native delivery (Terraform, containers, Kubernetes, CI/CD, automated deployment)
• Experience designing and developing large-scale distributed systems and cloud-native architectures
• Experience building large-scale infrastructure in Google Cloud, AWS, or Azure with Terraform
• Extensive experience implementing observability (Open Telemetry, Dynatrace, Grafana, etc)
• Strong problem-solving in complex systems
• Experience using AI-assisted development tools and validating AI outputs
• Understanding of responsible AI use in engineering workflows
• Strong ownership and proactive, self-motivated work style

• Cross-functional collaboration
• Strong problem-solving and troubleshooting
• Ownership and urgency
• Python
• Software Development Life Cycle
• Terraform

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