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Tier-1 brand, mid-level AI engineer title, metro location, and broad skills drive very high competition.
Core AI platform skills transfer across industries, but regulated financial services experience increases sensitivity.
Mandatory 5+ years, LLM and GCP expertise, and regulated environment make shortlisting highly selective.
Design, build, and maintain core components of Ford Credit's AI platform including agent frameworks, platform services, deployment pipelines, and knowledge capabilities.
Embed governance, security, and compliance controls to enable responsible AI development in a regulated financial services environment.
Collaborate cross-functionally with product, architecture, security, SRE, and business teams to deliver scalable, production-grade AI platform features and support internal customers from concept to production.
Bachelor's degree in Computer Science, Engineering, Data Science, Machine Learning, or related field (or equivalent experience).
5+ years of software engineering experience delivering production-grade applications and services.
Strong programming skills in Python and/or Java.
Experience developing cloud-native applications on Google Cloud Platform or comparable cloud environments, including hands-on use of LLMs, agent frameworks, retrieval systems, and tool integration.
Experienced software engineer comfortable building and operating AI platforms and developer tools in production, especially within regulated environments like financial services.
Practitioner of engineering best practices including testing, code quality, observability, and maintainability in complex cloud-native systems.
Collaborates closely with multi-disciplinary teams (product, security, architecture, SRE) to balance innovation with governance, security, and operational excellence.