At a Glance
- Tasks: Lead a team to develop innovative AI solutions and mentor junior engineers.
- Company: Join JPMorgan Chase, a leader in financial technology and innovation.
- Benefits: Competitive salary, diverse workplace, and opportunities for professional growth.
- Other info: Embrace diversity and inclusion in a dynamic, collaborative environment.
- Why this job: Shape the future of AI in Risk Technology and make a real impact.
- Qualifications: Degree in Computer Science or related field; experience in data science and NLQ.
The predicted salary is between 80000 - 100000 £ 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.
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- Agentic Gen AI / Natural Language Querying in Glasgow employer: 慨正橡扯
At JPMorgan Chase, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the field of AI technology. Our commitment to employee growth is evident through mentorship opportunities and a focus on continuous learning, ensuring that our team members thrive in their careers while contributing to impactful projects in Risk Technology. Located in a vibrant environment, we celebrate diversity and inclusion, making it a rewarding place for talented individuals to make a meaningful difference.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Software Engineer- Agentic Gen AI / Natural Language Querying in Glasgow
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those at JPMorgan Chase. A friendly chat can open doors and give you insights that might just land you an interview.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a GitHub repository showcasing your projects related to AI and natural language querying. This is your chance to demonstrate your expertise and creativity beyond the CV.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on your coding skills and system design principles. Use platforms like LeetCode or HackerRank to sharpen your problem-solving abilities.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in being part of our team at JPMorgan Chase.
We think you need these skills to ace Lead Software Engineer- Agentic Gen AI / Natural Language Querying in Glasgow
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 AI, software engineering, and any relevant projects you've led. We want to see how you can drive innovation in generative AI!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI solutions and how your background makes you a perfect fit for the Lead Software Engineer role. Let us know how you can contribute to our team!
Showcase Your Technical Skills:Don’t forget to mention your proficiency in Python, AWS, and any experience with tools like LangGraph. We’re looking for someone who can hit the ground running, so make sure we see your technical chops in your application.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team at StudySmarter!
How to prepare for a job interview at 慨正橡扯
✨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
Prepare examples of how you've led teams or mentored junior engineers in the past. Highlight your ability to foster a culture of excellence and continuous learning, as this is crucial for the role.
✨Understand the Business Impact
Be ready to discuss how your technical skills can drive business value, particularly in Risk Technology. Think about how generative AI and natural language querying can enhance decision-making processes in asset and wealth management.
✨Communicate Clearly
Practice explaining complex technical concepts in simple terms. You’ll need to communicate effectively with both technical and non-technical stakeholders, so being able to break down your ideas will be key to making a good impression.