Senior Lead Software Engineer, Inference Platform Engineer

JPMorgan Chase

Confirmed live today Low trust

Quick summary

Work type: On-site
Location: Seattle, WA
Employment: Full-time
Posted: 57 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $165k

$109k $220k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $151,000–$179,062.

Based on 240 similar postings.

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About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1226 open roles on FindRole.

Listed pay typically runs $156,750–$215,000 across 5 roles with salary data.

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At a glance

TL;DR · Senior Lead Software Engineer, Inference Platform Engineer

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As a Senior Lead Software Engineer- Inference Platform Engineer within the Infrastructure Platforms team, you will join an agile team focused on delivering secure, scalable technology products. You will architect and deploy cloud platforms optimized for AI/ML workloads, translating compute needs into infrastructure requirements while managing cloud resources for performance and cost efficiency. Your daily responsibilities include developing production code, reviewing others' work, and building CI/CD pipelines and infrastructure-as-code to streamline ML deployment. You will utilize Python, Go, Java, or C# alongside Kubernetes, Docker, and observability tools like Prometheus and Grafana. The role involves solving complex problems in high-performance LLM inference platforms, leveraging vLLM and GPU optimization to provide low-latency, high-throughput model serving while ensuring responsible AI use and secure coding practices.

Skills

Kubernetes Docker Python Go Java C# Infrastructure as Code CI/CD ML Ops MLflow Prometheus Grafana vLLM Microservices IaaS PaaS SaaS NVIDIA GPU Transformer Architecture SDLC

What you'll do

Develop secure, high-quality production code and perform code reviews for other engineers.
Architect and deploy secure, scalable cloud platforms optimized for AI/ML workloads.
Build CI/CD pipelines, automation, and infrastructure-as-code to streamline ML deployment.
Monitor and optimize cloud resources for performance and cost efficiency.
Translate AI team compute needs into specific infrastructure requirements.
Drive adoption and governance of approved AI-assisted engineering practices across teams.
Provide technical guidance and influence product design and technical operations.
Establish measurable validation standards for secure coding, peer review, and automated testing.

What we're looking for

Formal training or certification on software engineering concepts and 5+ years of applied experience.
Hands-on experience in system design, application development, testing, and operational stability.
Strong experience with Kubernetes and containerization (Docker), including cluster operations and production troubleshooting.
Proficiency in at least one programming language, such as Python, Go, Java, or C#.
Strong knowledge of cloud computing delivery models (IaaS, PaaS, SaaS) and deployment models (Public, Private, Hybrid Cloud).
Foundational understanding of machine learning concepts, including transformer architecture, ML training, and inference.
Experience with Infrastructure as Code and deep understanding of microservices, storage, security, and routing/switching technologies.
Demonstrated experience leading the use of enterprise-authorized AI-assisted software development tools and coaching others on compliant usage.

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