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 home office possible
TwinThread

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 Asset and Wealth Management while making 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: TwinThread

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.

TwinThread

Contact Detail:

TwinThread Recruiting Team

StudySmarter Expert Advice🤫

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

Network Like a Pro

Get out there and connect with folks in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works at JPMorgan Chase. Building relationships can open doors that a CV just can't.

Show Off Your Skills

Don’t just talk about your experience; demonstrate it! Create a portfolio showcasing your projects, especially those involving generative AI or natural language querying. This will give you an edge and show that you’re not just all talk.

Ace the Interview

Prepare for technical interviews by brushing up on your coding skills and understanding of AI frameworks. Practice common interview questions and be ready to discuss your past projects in detail. Confidence is key!

Apply Through Our Website

Make sure to apply directly through our website! It’s the best way to ensure your application gets seen by the right people. Plus, you’ll find all the latest job openings tailored to your skills.

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
AWS
LangGraph

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 in generative AI and how you've driven innovation in past projects.

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’ve applied these skills in real-world scenarios, so be specific!

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 TwinThread

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 will show that you're not just familiar with the tech but can also lead a team in using it effectively.

Showcase Your Leadership Skills

Since this role involves mentoring junior engineers, be prepared to share examples of how you've guided teams in the past. Talk about specific instances where your leadership made a difference, whether it was through technical guidance or fostering a culture of continuous learning.

Communicate Clearly

You’ll need to explain complex technical concepts to both technical and non-technical stakeholders. Practice articulating your thoughts clearly and concisely. Use examples from your previous work to demonstrate how you’ve successfully communicated ideas to diverse audiences.

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 experience with tools like LangGraph and Terraform. Consider doing mock interviews to get comfortable with potential technical questions.