Lead Software Engineer- Agentic Gen AI / Natural Language Querying in London

Lead Software Engineer- Agentic Gen AI / Natural Language Querying in London

London Full-Time 80000 - 100000 £ / year (est.) No working from home possible
Aumni

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: Inclusive culture that values diversity and promotes continuous learning.
  • 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 in London employer: Aumni

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 diversity and inclusion, ensuring that every team member can thrive and contribute meaningfully to the future of Asset and Wealth Management Risk. Located in a vibrant city, our team enjoys access to cutting-edge resources and a supportive environment that encourages continuous learning and professional development.

Aumni

Contact Details:

Aumni Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Lead Software Engineer- Agentic Gen AI / Natural Language Querying in London

Tip Number 1

Network like a pro! Reach out to your connections in the industry, attend meetups, and engage in online forums. 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 bring to the table.

Tip Number 3

Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions and be ready to discuss your experience with tools like LangGraph and AWS.

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 joining our team at StudySmarter.

We think you need these skills to ace Lead Software Engineer- Agentic Gen AI / Natural Language Querying in London

Generative AI
Agentic AI
Natural Language Querying (NLQ)
Data Science
Python
System Design
Application Development

Some tips for your application 🫡

Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your experience with 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 AI and how your background makes you a great fit for the role. Share specific examples of your work that align with our mission at StudySmarter.

Showcase Your Technical Skills:Don’t forget to mention your proficiency in Python and any experience with AWS or LangGraph. We want to see how you can contribute to our tech stack and help drive innovation in generative AI.

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 your enthusiasm for joining our team!

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 end-to-end pipelines, especially on AWS. This shows you're not just familiar with the tech but can also apply it effectively.

Showcase Your Leadership Skills

Since this role involves mentoring and guiding junior engineers, be prepared to share examples of how you've led teams in the past. Talk about specific challenges you faced and how you helped your team overcome them. This will demonstrate your ability to foster a culture of excellence.

Communicate Clearly

You’ll need to explain complex technical concepts to both technical and non-technical stakeholders. Practice simplifying your explanations without losing the essence of the technology. This skill is crucial for ensuring everyone is on the same page, especially when collaborating with cross-functional partners.

Prepare for Technical Questions

Expect to dive deep into system design and application development during the interview. Brush up on your Python skills and be ready to discuss your hands-on experience with tools like LangGraph and Terraform. Being able to articulate your thought process will impress the interviewers.