At a Glance
- Tasks: Lead AI projects, mentor engineers, and develop innovative solutions for risk technology.
- Company: Join JPMorgan Chase, a leader in financial services with a focus on diversity and inclusion.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Dynamic environment with a commitment to continuous learning and career advancement.
- Why this job: Make a real impact in AI while working with cutting-edge technologies and talented teams.
- Qualifications: Degree in Computer Science or related field; strong Python and data science skills required.
The predicted salary is between 80000 - 100000 £ per year.
As a Lead Software Engineer for AI - Vice President at JPMorgan Chase in Risk Technology, you will lead a specialized technical area, driving impact across teams, technologies, and projects. You will leverage your expertise in software engineering, multi-agent system design, data science, and NLQ to deliver complex, high-impact initiatives. You will mentor and guide a team of engineers, foster best practices in AI engineering, and partner with data science, product, and business teams to deliver end-to-end solutions that drive value for the Risk business.
Job Responsibilities
- Lead the deployment and scaling of advanced generative AI and agentic AI solutions for the Risk business, with a focus on natural language querying of structured and unstructured data sources.
- Design and execute enterprise-wide, reusable AI frameworks and core infrastructure to accelerate AI solution development, including NLQ capabilities for diverse data types.
- Develop multi-agent systems for orchestration, agent-to-agent communication, memory, telemetry, guardrails, and NLQ-driven data retrieval and processing.
- Guide research on context and prompt engineering techniques to improve prompt-based model performance and NLQ accuracy, utilizing libraries such as LangGraph.
- Develop and maintain tools and frameworks for prompt-based agent evaluation, monitoring, and optimization at enterprise scale, with emphasis on NLQ workflows and orchestration.
- Build and maintain data pipelines and processing workflows for scalable, efficient consumption and querying of structured and unstructured data via natural language interfaces.
- Write secure, high-quality production code and conduct code reviews.
- Partner with Data Science, Product, and Business teams to identify requirements and develop NLQ-enabled solutions.
- Communicate technical concepts and results to both technical and non-technical stakeholders, including senior leadership.
- Provide technical leadership, mentorship, and guidance to junior engineers, promoting a culture of excellence and continuous learning.
Required Qualifications, Capabilities, And Skills
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
- Experience in data science and natural language querying, including experience deploying end-to-end pipelines on AWS.
- Strong proficiency in Python.
- Hands-on experience in system design, application development, testing, and operational stability.
- Experience using LangGraph for multi-agent orchestration and NLQ integration.
- Experience with AWS and infrastructure-as-code tools such as Terraform.
Preferred Qualifications, Capabilities, And Skills
- Strategic thinker with the ability to drive technical vision for business impact.
- Experience with agentic telemetry, evaluation services, and orchestration of NLQ workflows.
- Demonstrated leadership working with engineers, data scientists, and AI practitioners.
- Familiarity with MLOps practices and AI pipelines.
- Hands-on experience building and maintaining user interfaces for NLQ and data exploration.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.
Lead Software Engineer - AI for Risk Technology employer: JPMorganChase
At JPMorgan Chase, we pride ourselves on being an exceptional employer, particularly for our Lead Software Engineer - AI role in Risk Technology. Our inclusive work culture fosters collaboration and innovation, providing ample opportunities for professional growth and mentorship within a diverse team. Located in a dynamic environment, we offer competitive benefits and the chance to work on cutting-edge AI solutions that have a meaningful impact on the financial industry.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Software Engineer - AI for Risk Technology
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repo showcasing your projects, especially those related to AI and software engineering. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios. We recommend doing mock interviews with friends or using online platforms to get comfortable with the process.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team.
We think you need these skills to ace Lead Software Engineer - AI for Risk Technology
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your expertise in software engineering, AI, and data science, as these are key areas for us at StudySmarter.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a great fit for the Lead Software Engineer role. We love seeing genuine enthusiasm!
Showcase Your Projects:If you've worked on relevant projects, especially those involving multi-agent systems or natural language querying, make sure to include them. We want to see what you've built and how it can impact our work at StudySmarter.
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’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at JPMorganChase
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python, AWS, and LangGraph. Brush up on your experience with multi-agent systems and natural language querying, as these will be key topics during your interview.
✨Showcase Your Leadership Skills
As a Lead Software Engineer, you'll need to demonstrate your ability to mentor and guide a team. Prepare examples of how you've successfully led projects or teams in the past, focusing on fostering best practices and driving technical vision.
✨Prepare for Technical Questions
Expect in-depth technical questions related to system design, application development, and operational stability. Practice explaining complex concepts clearly, as you’ll need to communicate effectively with both technical and non-technical stakeholders.
✨Demonstrate Your Strategic Thinking
Be ready to discuss how you can drive business impact through technology. Think about past experiences where your strategic decisions led to successful outcomes, and be prepared to share those insights during the interview.
