Senior Lead Software Engineer-AI Foundation Services
Salary not listed • Plano, TX, United States • Full-time
Posted 15d ago
No salary is listed. Many US states require employers to post a pay range, so ask about pay early.
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Infrastructure Engineer
About the job
JPMorgan Chase's Chief Data & Analytics (AIML Data Platforms) team is seeking a Senior Lead Software Engineer to build AI foundation services for GenAI and ML at an enterprise scale. This role involves leading the hands-on delivery of secure, reliable, cloud-native platform capabilities, including Kubernetes, CI/CD, and Infrastructure as Code. You will partner with application teams to create reusable integrations, reference implementations, and onboarding assets, driving significant business impact through deep technical expertise and problem-solving across diverse technologies.
Responsibilities
- Design, build, integrate, and optimize AI Foundation Services infrastructure components for GenAI and traditional AI/ML platforms with a focus on production-quality delivery.
- Partner with Lines of Business (LOB) application teams to co-develop reusable AI/ML foundational service capabilities, managed service integrations, and platform adoption patterns.
- Translate LOB application requirements into clear technical designs, implementation plans, and engineering deliverables for successful launch and operational readiness.
- De-risk AI/ML platform delivery across performance, scale, reliability, and security by contributing to non-functional requirements, test plans, runbooks, observability, and production readiness reviews.
- Build reusable engineering assets such as reference implementations, deployment templates, test harnesses, onboarding guides, and GPU/training/serving baselines for model hosting platforms.
- Drive adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes.
- Implement durable, maintainable code solutions and production platform capabilities reusable by multiple application teams.
- Collaborate with product, platform, security, infrastructure, and application teams to resolve complex technical issues and deliver AI Foundation Services capabilities aligned to business priorities.
- Participate in technical design reviews, operational readiness reviews, incident analysis, and continuous improvement activities.
Requirements
- Formal training or certification on software engineering concepts and 5+ years of applied experience.
- Hands-on experience designing, building, testing, and operating production software systems, distributed services, or platform capabilities.
- Practical experience with AI/ML platform capabilities, model serving, model hosting, data access patterns, platform integrations, or infrastructure services supporting AI/ML workloads.
- Experience developing cloud-native applications or platform services using Kubernetes, containers, CI/CD, infrastructure-as-code, and modern engineering practices.
- Proficiency in one or more programming languages such as Python, Java, Go, or similar, with demonstrated ability to deliver high-quality production code.
- Experience translating business or application team requirements into technical designs, implementation tasks, delivery milestones, and operational support plans.
- Working knowledge of performance engineering and production reliability practices, including load testing, capacity planning, monitoring, alerting, SLOs/SLIs, incident response, and root-cause analysis.
- Experience applying secure-by-design engineering practices, including access controls, secrets management, vulnerability remediation, and secure handling of sensitive data.
- Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment.
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.
- Demonstrated ability to collaborate across product, application, infrastructure, and security teams to deliver complex technical outcomes.