At a Glance
- Tasks: Lead AI projects, mentor engineers, and develop innovative solutions for risk technology.
- Company: Join JPMorgan Chase, a leader in financial services with a focus on technology.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Other info: Dynamic work environment with excellent career advancement opportunities.
- Why this job: Make a real impact in AI while working with cutting-edge technologies and talented teams.
- Qualifications: Degree in Computer Science or related field; experience in data science and Python required.
The predicted salary is between 70000 - 90000 £ per year.
As a Lead Software Engineer for AI – 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.
Lead Software Engineer - AI for Risk Technology employer: Jpmorgan Chase & Co.
At JPMorgan Chase, we pride ourselves on being an exceptional employer, particularly for those in the Lead Software Engineer role within our Risk Technology team. Our collaborative work culture fosters innovation and continuous learning, providing ample opportunities for professional growth while working on cutting-edge AI solutions that have a significant impact on the financial industry. Located in a dynamic environment, employees benefit from a strong support system, mentorship from experienced leaders, and the chance to contribute to transformative projects that drive value across the organisation.
