Senior Lead Software Engineer- Platform / Linux Engineering
Hands-on senior platform engineer at JPMorganChase designing, building, and tuning Linux compute infrastructure for low-latency electronic trading — kernel tuning, CPU/NUMA optimization, kernel-bypass networking (Solarflare Onload), plus production automation in Python/Go and infrastructure-as-code, while driving AI-assisted engineering practices and mentoring teams.
- Compensation
- Not disclosed
- Location
- New York, NY, United States
- Work setup
- Not specified
- Seniority
- Lead
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Software engineering
- Posted
Skills
Must have
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Strong programming skills for production-grade tooling and automation (e.g., Python, Go, Bash)
- Deep hands-on Linux engineering: administration, internals, performance tuning, benchmarking (e.g., Red Hat Enterprise Linux)
- Proven experience engineering for low-latency, high-throughput environments (kernel tuning, CPU/NUMA optimization, precision timing)
- Hands-on kernel-bypass networking experience, specifically Solarflare Onload
- Extensive configuration management experience (e.g., Chef or Ansible)
- Demonstrated experience leading use of enterprise-authorized AI-assisted development tools and setting standards for validating AI outputs
- Strong understanding of responsible AI use in engineering workflows (data sensitivity, secure handling of inputs/outputs)
- Solid understanding of IPv4 networking (OSI model, unicast/broadcast/multicast, routing, network segregation)
- Experience designing CI/CD pipelines and infrastructure-as-code (e.g., Terraform)
- Practical cloud-native and container/orchestration experience (e.g., Docker, Kubernetes)
- Experience leading cross-functional teams of technologists, hiring, developing, and recognizing talent
Nice to have
- Server hardware selection, BIOS/firmware tuning, and bare-metal provisioning for performance-sensitive workloads
- Familiarity with observability/telemetry stacks (Prometheus, Grafana, ELK) and standard cryptography (certificates, key pairs, secure communication)
- Experience with market-data and messaging technologies common to electronic trading (multicast market data, low-latency messaging buses)
- Experience with database management systems, preferably PostgreSQL
Full description
Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As a Senior Lead Software Engineer- Platform / Linux Engineering at JPMorganChase within the Corporate Sector- Infrastructure Platforms, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
As a Senior Platform Engineer within Electronic Trading Services Platforms, you will be a hands-on technical leader responsible for designing, building, and tuning the Linux-based compute and infrastructure platforms that power our low-latency electronic trading businesses. This is a deeply technical, engineering-first role: you will write code and automation, design new systems, architect novel deployment models, and drive latency out of the stack at the hardware, kernel, and network layers. You will also harness modern Agentic AI tooling to accelerate delivery and multiply your impact.
You will work directly with the Electronic Trading Lines of Business to align technical strategy with business goals, solve complex compute and performance-engineering challenges, and mentor partner technical teams. You will serve as an expert, hands-on advisor to peers, leadership, and stakeholders.
Job responsibilities
- Design, build, and operate high-performance Linux platforms for low-latency electronic trading, engineering from the hardware and kernel level up
- Architect new system designs and next-generation deployment models — including immutable infrastructure, containerization, and automated provisioning pipelines
- Perform deep performance engineering and latency optimization: kernel tuning, CPU isolation/pinning, NUMA awareness, IRQ affinity, kernel-bypass networking, and precision time synchronization
- Write production-quality code and automation to build tooling, eliminate manual toil, and improve platform reliability and speed
- Leverage Agentic AI tools and workflows to accelerate engineering tasks, automate research and remediation, and deliver against goals faster
- Drive adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain