Overview
Lead Software Engineer for AI – Vice President, in Risk Technology at JPMorgan Chase. You will lead a specialized technical area, drive impact across teams and projects, and mentor engineers in AI engineering, data science, and NLQ-focused initiatives. Partner with data science, product, and business teams to deliver end-to-end solutions that create value for the Risk business. You will deploy and scale advanced generative AI and agentic AI solutions with a focus on natural language querying of structured and unstructured data sources.
Responsibilities
- 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 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 ingestion, querying, and processing 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, fostering a culture of excellence and continuous learning.
Qualifications
- 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 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.
- 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.
About JPMorgan Chase
JPMorgan Chase is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.
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