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- Tasks: Lead a team to develop innovative AI solutions and mentor junior engineers.
- Company: Join J.P. Morgan, a global leader in financial services.
- Benefits: Competitive salary, diverse work culture, and opportunities for professional growth.
- Other info: Dynamic environment with a focus on diversity and inclusion.
- Why this job: Shape the future of AI in finance and make a real impact.
- Qualifications: Degree in Computer Science or related field; strong Python skills required.
The predicted salary is between 80000 - 100000 ÂŁ per year.
Are you passionate about building the next generation of AI solutions? Join us to lead and mentor a team of talented engineers, drive innovation in generative and agentic AI, and deliver impactful, scalable technology for Risk Technology. You’ll collaborate with cross‑functional partners and play a key role in shaping the future of Asset and Wealth Management Risk.
As a Lead Agentic Gen AI / Natural Language Querying Engineer – 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.
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first‑class business in a first‑class way approach to serving clients drives everything we do. We strive to build trusted, long‑term partnerships to help our clients achieve their business objectives. 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.
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.
Lead Software Engineer- Agentic Gen AI / NLP employer: JPMorganChase
Contact Detail:
JPMorganChase Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Software Engineer- Agentic Gen AI / NLP
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage with professionals on platforms like LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and NLP. This gives potential employers a tangible sense of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions and scenarios relevant to the role. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both techies and non-techies.
✨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 at JPMorgan Chase.
We think you need these skills to ace Lead Software Engineer- Agentic Gen AI / NLP
Some tips for your application 🫡
Show Your Passion: When writing your application, let your enthusiasm for AI and software engineering shine through. We want to see that you’re genuinely excited about building innovative solutions and leading a team.
Tailor Your Experience: Make sure to highlight your relevant experience in data science, natural language querying, and multi-agent systems. We love seeing how your background aligns with the role, so don’t hold back on those details!
Be Clear and Concise: Keep your application straightforward and to the point. Use clear language to communicate your skills and experiences, as we appreciate clarity just as much as technical expertise.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for this exciting opportunity.
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 and AWS. Brush up on your experience with LangGraph and multi-agent systems, as these will likely come up during technical discussions.
✨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 innovation.
✨Prepare for Cross-Functional Collaboration
You’ll be working with various teams, so be ready to discuss how you’ve collaborated with data scientists, product managers, and business stakeholders. Highlight any experiences where you effectively communicated complex technical concepts to non-technical audiences.
✨Think Strategically About AI Solutions
The role requires a strategic mindset, so come prepared with ideas on how to drive technical vision for business impact. Think about how you can leverage generative AI and NLQ to solve real-world problems in Risk Technology and be ready to share your thoughts.