Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead site reliability initiatives and mentor engineers in a dynamic tech environment.
- Company: Join JPMorgan Chase, a globally recognised firm shaping the future of technology.
- Benefits: Enjoy competitive pay, remote work options, and a vibrant company culture.
- Why this job: Make a significant impact on AI/ML systems while collaborating with top talent.
- Qualifications: Strong background in site reliability engineering and proficiency in programming languages required.
- Other info: Opportunity to work with cutting-edge technologies and participate in incident management.
The predicted salary is between 36000 - 60000 £ per year.
Assume a critical role in defining the future of a globally recognized firm and have a direct and significant effect in a realm tailored for top achievers in site reliability. As an AI ML Lead Site Reliability Engineer at JPMorgan Chase within the AIML Data Platform Team, you hold a leadership role in your team, demonstrate strong knowledge across multiple technical domains, and advise others on the technical and business issues facing them.
Take lead and conduct resiliency design reviews, break up complex problems into digestible work for other engineers, act as a technical lead for medium to large-sized products, and provide advice and mentoring to other engineers.
Responsibilities include:
- Demonstrating and championing site reliability culture and practices, exerting technical influence throughout your team
- Leading initiatives to improve the reliability and stability of applications and platforms using data-driven analytics
- Collaborating to identify service level indicators and establish service level objectives and error budgets with stakeholders
- Exhibiting high technical expertise and proactively solving technology-related bottlenecks
- Acting as the main contact during major incidents to identify and resolve issues promptly
- Partnering with product engineering teams to ensure reliability and performance of AI/ML systems
- Developing observability, security, automation, and fin-ops tools and orchestration
- Providing strategic technology leadership and defining standards for reliability and automation frameworks
- Building cross-functional relationships to deliver solutions and resolve user problems
- Debugging and solving production issues, identifying root causes, and remediating
- Participating in on-call rotations, incident management, and escalation workflows
Required qualifications include:
- Formal training or certification in site reliability engineering concepts and applicable experience
- Deep proficiency in reliability, scalability, performance, security, and enterprise system architecture
- Fluency in programming languages such as Python, Java Spring Boot, or .Net
- Deep knowledge of software applications and technical processes, with emerging expertise in specific disciplines
- Proficiency in observability tools such as Grafana, Dynatrace, Prometheus, Datadog, Splunk
- Experience with CI/CD tools like Jenkins, GitLab, Terraform
- Experience with containerization and orchestration tools such as ECS, Kubernetes, Docker
- Expertise in SRE principles, reliability, scalability, and performance of applications and infrastructure
- Proficiency in Python programming and Infrastructure as Code tools like Terraform
- Experience designing distributed systems and cloud-native architectures in AWS
- Self-motivated with a strong sense of ownership and urgency
Preferred qualifications include: prior experience in AI, ML, or Data engineering, expertise in Kubernetes, automation frameworks, and observability/telemetry tools.
AI ML Lead Site Reliability Engineer employer: TN United Kingdom
Contact Detail:
TN United Kingdom Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI ML Lead Site Reliability Engineer
✨Tip Number 1
Familiarise yourself with the latest trends in AI and ML, especially as they relate to site reliability engineering. This knowledge will not only help you during interviews but also demonstrate your passion for the field.
✨Tip Number 2
Network with professionals in the industry, particularly those working in AI and ML roles. Attend relevant meetups or webinars to build connections that could lead to referrals or insider information about the job.
✨Tip Number 3
Showcase your technical skills through personal projects or contributions to open-source projects. This practical experience can set you apart from other candidates and provide concrete examples of your capabilities.
✨Tip Number 4
Prepare for technical interviews by practising problem-solving scenarios related to site reliability. Focus on how you would approach real-world issues, as this will highlight your critical thinking and technical expertise.
We think you need these skills to ace AI ML Lead Site Reliability Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in site reliability engineering, AI, and ML. Focus on your technical skills, particularly in programming languages like Python and Java, as well as your experience with observability tools and CI/CD processes.
Craft a Compelling Cover Letter: Write a cover letter that showcases your leadership abilities and your understanding of site reliability culture. Mention specific projects where you've improved application reliability or stability, and how your expertise aligns with the responsibilities outlined in the job description.
Showcase Technical Expertise: In your application, provide examples of your proficiency in relevant technologies such as Kubernetes, Docker, and Terraform. Highlight any certifications or formal training you have in site reliability engineering concepts to strengthen your application.
Demonstrate Problem-Solving Skills: Include instances where you've successfully debugged production issues or led initiatives to enhance system performance. This will illustrate your ability to tackle complex problems and your proactive approach to technology-related challenges.
How to prepare for a job interview at TN United Kingdom
✨Showcase Your Technical Expertise
As an AI ML Lead Site Reliability Engineer, you'll need to demonstrate your deep proficiency in reliability, scalability, and performance. Be prepared to discuss specific projects where you've applied these skills, particularly with tools like Grafana or Kubernetes.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities in real-world situations. Think about past incidents you've managed, how you identified root causes, and the steps you took to resolve them. This will showcase your experience in incident management.
✨Emphasise Collaboration Skills
Highlight your ability to work cross-functionally with product engineering teams. Discuss how you've previously partnered with stakeholders to establish service level objectives and improve application reliability, as this is crucial for the role.
✨Demonstrate Leadership Qualities
Since this role involves mentoring and leading initiatives, be ready to share examples of how you've guided teams or influenced technical decisions. Show that you can take ownership and drive improvements in site reliability practices.
