At a Glance
- Tasks: Lead a team to develop innovative AI solutions and natural language querying systems.
- 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 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 £ 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.
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 employer: Aumni
At JPMorgan Chase, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As a Lead Software Engineer in our Risk Technology team, you will have the opportunity to lead cutting-edge AI projects while mentoring talented engineers, all within a diverse and inclusive environment that values your unique contributions. With a strong focus on employee growth and development, we provide ample opportunities for professional advancement and the chance to make a meaningful impact in the world of Asset and Wealth Management.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Software Engineer- Agentic Gen AI / Natural Language Querying
✨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 natural language querying. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions and scenarios related to generative AI and data pipelines. 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 StudySmarter.
We think you need these skills to ace Lead Software Engineer- Agentic Gen AI / Natural Language Querying
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Lead Software Engineer role. Highlight your experience in AI solutions, natural language querying, and any relevant projects you've led or contributed to.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about generative AI and how your background makes you a great fit for our team. Be sure to mention specific technologies and frameworks you've worked with, like LangGraph or AWS.
Showcase Your Leadership Skills:Since this role involves mentoring and guiding junior engineers, share examples of how you've led teams or projects in the past. We want to see your ability to inspire and drive innovation within a team.
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Aumni
✨Know Your AI Stuff
Make sure you brush up on the latest trends in generative and agentic AI. Be ready to discuss your experience with natural language querying and how you've deployed AI solutions in the past. This will show that you're not just familiar with the tech, but that you're genuinely passionate about it.
✨Showcase Your Leadership Skills
Since this role involves mentoring a team, be prepared to share examples of how you've led projects or guided junior engineers. Highlight your ability to foster a culture of excellence and continuous learning, as this is key for the position.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions, especially around Python, AWS, and tools like LangGraph. Practise explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical stakeholders.
✨Demonstrate Strategic Thinking
Think about how your technical vision can drive business impact. Be ready to discuss how you've approached problem-solving in the past and how you plan to contribute to the future of Asset and Wealth Management Risk through innovative AI solutions.