AI Platform Engineer
Talent Groups
About the role
Hybrid Details
Onsite 3 days/week
Job Description
We are looking for an AI Platform Engineer to help define how engineers build with AI across our organization. In this role, you’ll sit at the intersection of Generative AI and platform engineering, designing the tools, workflows, and standards that make it easy for developers to build, deploy, and scale AI‑powered applications. Your work will directly shape how teams adopt and use AI making it more accessible, reliable, and impactful.
You’ll join a lean, high‑impact team where collaboration is key. We work closely with engineering, infrastructure, and security partners to ensure the solutions we build are scalable, secure, and solve real‑world problems.
What You'll Do
- Define the AI Development Lifecycle: Establish and evolve the end‑to‑end AI development lifecycle, including guardrails, context management, and engineering standards that enable responsible and efficient AI adoption.
- Drive Adoption & Alignment: Lead cross‑functional initiatives that improve how teams build and ship software, with a focus on scaling AI capabilities and enhancing developer experience.
- Build for Developers: Design and deliver self‑service capabilities that simplify how engineers build, test, and deploy applications—especially AI‑powered ones. This includes reusable tooling, templates, and patterns that reduce friction and accelerate delivery.
- Raise the Engineering Bar: Set and uphold high standards for platform and AI engineering. Mentor engineers and stakeholders, and promote clean, scalable, and maintainable design practices.
- Think Like a Product Owner: Treat internal platforms and AI capabilities as products. Continuously iterate based on developer feedback, usability, and adoption metrics.
- Enable AI at Scale: Develop the foundational components that allow teams to safely and effectively leverage AI, including shared services, reusable modules, and well‑defined integration patterns.
- Simplify Delivery & Deployment: Improve CI/CD workflows and streamline how applications are built and deployed, enabling teams to ship reliable software faster.
- Improve Reliability & Operations: Strengthen system reliability and operational excellence, ensuring platforms are stable, observable, and easy to support.
What You Bring
- 7+ years of software development experience
- Strong programming skills and engineering fundamentals
- Experience with modern software delivery practices (CI/CD, cloud environments, etc.)
- Familiarity or interest in AI/ML systems, particularly LLM‑based applications
- Strong problem‑solving skills and attention to detail
- Ability to collaborate across teams and influence without direct authority
- Curiosity and a continuous learning mindset
#LI-Hybrid
Requirements
- 7+ years of software development experience
- Strong programming skills and engineering fundamentals
- Experience with modern software delivery practices (CI/CD, cloud environments, etc.)
- Familiarity or interest in AI/ML systems, particularly LLM-based applications
- Strong problem-solving skills and attention to detail
- Ability to collaborate across teams and influence without direct authority
- Curiosity and a continuous learning mindset
Responsibilities
- Define the AI Development Lifecycle: Establish and evolve the end-to-end AI development lifecycle, including guardrails, context management, and engineering standards that enable responsible and efficient AI adoption.
- Drive Adoption & Alignment: Lead cross-functional initiatives that improve how teams build and ship software, with a focus on scaling AI capabilities and enhancing developer experience.
- Build for Developers: Design and deliver self-service capabilities that simplify how engineers build, test, and deploy applications—especially AI-powered ones. This includes reusable tooling, templates, and patterns that reduce friction and accelerate delivery.
- Raise the Engineering Bar: Set and uphold high standards for platform and AI engineering. Mentor engineers and stakeholders, and promote clean, scalable, and maintainable design practices.
- Think Like a Product Owner: Treat internal platforms and AI capabilities as products. Continuously iterate based on developer feedback, usability, and adoption metrics.
- Enable AI at Scale: Develop the foundational components that allow teams to safely and effectively leverage AI, including shared services, reusable modules, and well-defined integration patterns.
- Simplify Delivery & Deployment: Improve CI/CD workflows and streamline how applications are built and deployed, enabling teams to ship reliable software faster.
- Improve Reliability & Operations: Strengthen system reliability and operational excellence, ensuring platforms are stable, observable, and easy to support.
Skills
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