Senior Lead Software Engineer - Python, AI & LLM
JPMorgan Chase6 hours ago
Glasgow, United KingdomStaff+
Responsibilities
- Lead the design and delivery of platform standards and tooling, including command-line interfaces, software development kits, libraries, templates, and automated checks.
- Build and operate production large language model inference services using serving engines such as vLLM, TensorRT-LLM, SGLang, or LLM-D.
- Design Kubernetes deployment, scaling, networking, and troubleshooting practices for reliable platform operations.
- Optimize inference performance through GPU memory analysis, key-value cache sizing, memory bandwidth and compute trade-off evaluation, and inference-time quantization.
- Implement secure production code and automation that improves resiliency, observability, and operational readiness.
- Create and maintain architecture and design artifacts while enforcing non-functional requirements through implementation and automation.
- Guide adoption of enterprise-authorized AI-assisted engineering practices, validation standards, and reusable development patterns.
- Mentor engineers and provide technical direction while partnering with platform and product stakeholders.
Requirements
- Hands-on experience building platform standards and developer tooling such as command-line interfaces, software development kits, libraries, templates, and automated checks.
- Deep production experience with large language model inference systems and serving engines such as vLLM, TensorRT-LLM, SGLang, or LLM-D.
- Experience building and operating production services on public cloud platforms such as AWS.
- Ability to design, deploy, and troubleshoot AWS compute, storage, networking, identity, and access infrastructure.
- Demonstrated expertise with Kubernetes deployments, scaling, networking, and troubleshooting.
- Working knowledge of GPU memory architecture, key-value cache behavior, memory bandwidth, and compute bottlenecks.
- Understanding of inference-time quantization and its effects on latency, throughput, cost, and serving quality.
- Ability to produce architecture and design artifacts and implement secure, scalable solutions.
- Strong understanding of software development lifecycle, continuous integration and delivery, resiliency, and security practices.
- Hands-on experience using enterprise-authorized AI-assisted software development tools and validating their outputs for correctness, performance, and security.
- Understanding of responsible AI use in engineering workflows, including data sensitivity and secure input and output handling.
- Preferred experience with shared platform capabilities, model lifecycle tooling, safe deployment and rollback, inference monitoring, SLOs, error budgets, service mesh, advanced Kubernetes traffic management, and developer self-service workflows.
Tech Stack
Categories
About JPMorgan Chase
JPMorgan Chase provides consumer and commercial banking, payments, credit card, wealth management, and corporate and investment banking services to individuals, businesses, institutions, and governments. The public company (NYSE: JPM) earns revenue from interest, fees, trading, and asset management across operations in more than 100 markets. Headquartered in New York City with roots dating to 1799, it serves retail customers and prominent corporate and government clients through brands including Chase and J.P. Morgan.