Lead Software Engineer for AI – Vice President at JPMorgan Chase
In the Risk Technology division, 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.
Equal Opportunity Employment Statement
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. Visit our FAQs for more information about requesting an accommodation.
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