At a Glance
- Tasks: Lead AI engineering projects and mentor a team of talented engineers.
- Company: Join JPMorgan Chase, a leader in financial services and technology.
- Benefits: Attractive salary, comprehensive benefits, and opportunities for professional growth.
- Other info: Dynamic role with leadership opportunities in a fast-paced environment.
- Why this job: Shape the future of AI in risk technology and make a significant impact.
- Qualifications: Expertise in software engineering, data science, and strong Python and AWS skills.
The predicted salary is between 80000 - 100000 £ per year.
JPMorgan Chase is seeking a Lead Software Engineer for AI - Vice President in Risk Technology. In this role, you will drive impact through advanced AI solutions, mentor engineers, and collaborate across teams to deliver end-to-end value for the Risk business.
The ideal candidate has expertise in software engineering, data science, and multi-agent systems with strong skills in Python and AWS. This position emphasizes leadership and strategic vision in AI deployment.
Head of AI Engineering — Risk Tech & NLQ Innovator employer: Fairygodboss
JPMorgan Chase is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the rapidly evolving field of AI. With a strong emphasis on employee growth, you will have access to mentorship opportunities and cutting-edge projects that drive meaningful impact in Risk Technology. Located in a vibrant city, our team enjoys a supportive environment that values diversity and encourages creative problem-solving.
StudySmarter Expert Advice🤫
We think this is how you could land Head of AI Engineering — Risk Tech & NLQ Innovator
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. We can’t stress enough how important it is to make connections that could lead to job opportunities.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your AI projects and coding prowess. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios related to AI engineering. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Head of AI Engineering — Risk Tech & NLQ Innovator
Some tips for your application 🫡
Show Your Passion for AI:When writing your application, let your enthusiasm for AI and its potential shine through. We want to see how you can drive impact with advanced AI solutions, so share any relevant projects or experiences that highlight your passion.
Highlight Your Leadership Skills:As a Head of AI Engineering, you'll be mentoring engineers and leading teams. Make sure to showcase your leadership experience in your application. We’re looking for examples where you've guided others and made strategic decisions in tech.
Tailor Your Application:Don’t just send a generic application! We want to see how your skills in software engineering, data science, and multi-agent systems align with our needs. Customise your CV and cover letter to reflect the job description and demonstrate why you're the perfect fit.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at Fairygodboss
✨Showcase Your AI Expertise
Make sure to highlight your experience with AI solutions and how you've driven impact in previous roles. Be ready to discuss specific projects where you implemented advanced AI techniques, especially in risk technology.
✨Demonstrate Leadership Skills
Since this role emphasises leadership, prepare examples of how you've mentored engineers or led teams. Think about times when you provided strategic vision for AI deployment and how that benefited the project or company.
✨Brush Up on Technical Skills
Given the focus on software engineering and data science, ensure you're comfortable discussing Python and AWS. Be prepared to answer technical questions or even solve problems on the spot to showcase your coding skills.
✨Collaborative Mindset
This position requires collaboration across teams, so be ready to talk about your experiences working with cross-functional teams. Share how you’ve successfully communicated complex AI concepts to non-technical stakeholders.
