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This listing doesn't post a salary. Most similar roles pay
$142,400–$208,642.
Based on 240 similar postings.
Employer
About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
JPMorgan Chase currently has
1226 open roles
on FindRole.
Listed pay typically runs
$156,750–$215,000
across 5 roles with salary data.
Lead Software Engineer - Ai Engineer joins the Automation & AI Solutions team within the Commercial & Investment Bank. In this role, you will architect, design, and deliver scalable software products that integrate cloud-native microservices with generative AI and LLM capabilities. Your daily responsibilities include developing full-stack solutions, leading the implementation of AI-driven services and orchestration, and driving the adoption of AI-assisted engineering practices to improve code quality and delivery speed. You will work with Java, AWS ECS, EKS, Postgres, and Python, while utilizing tools like CoPilot, Claude, PyTorch, TensorFlow, and Hugging Face. You will solve complex technical problems by building RESTful APIs, managing distributed systems, and ensuring responsible AI use through secure coding standards, RAG, and prompt orchestration within a production environment.
Architect and deliver scalable cloud-native microservices and APIs using Java, AWS, and Postgres.
Design and implement AI-driven capabilities including LLM-based services, orchestration, and business workflow integrations.
Lead the adoption of enterprise-authorized AI coding tools to improve code quality, delivery speed, and productivity.
Establish validation standards for AI-generated outputs, including secure coding, peer reviews, and automated testing.
Identify and automate solutions for recurring operational issues to improve system stability and observability.
Influence product design and technical operations by proposing architectures aligned with firm security and SDLC standards.
Manage project priorities and communicate status across multiple initiatives within a Scrum team environment.
What we're looking for
Formal training or certification in Software Engineering and 5+ years of applied experience.
Strong system design, application development, and operational stability skills in production environments.
Hands-on experience using enterprise-authorized AI-assisted software development tools to create, validate, and refine outputs for security and performance.
Understanding of responsible AI use, including data sensitivity, secure handling of inputs/outputs, and adherence to resiliency expectations.
Hands-on experience with Large Language Models (LLMs) and generative AI use cases like RAG, agents, and prompt orchestration.
Familiarity with AI/ML frameworks such as PyTorch, TensorFlow, scikit-learn, and Hugging Face.
Experience with distributed systems, cloud platforms (AWS, GCP, or Azure), microservices, RESTful APIs, and relational or NoSQL data technologies.
Practical experience building cloud-native systems including event-driven architectures, streaming, and service mesh.
Cloud certification in AWS, GCP, or Azure (preferred).
Working knowledge of Python for AI/ML integrations (preferred).
Familiarity with Docker, Kubernetes, Helm, and modern CI/CD practices (preferred).
Python
Java
Large Language Models
Generative AI
MLOps
RAG
Vector Databases
AWS
GCP
Azure
Microservices
APIs
Data Pipelines
Distributed Systems
Agile
OCR
Semantic Search
Embeddings