LOG IN
SIGN UP
Canary Wharfian - Online Investment Banking & Finance Community.
Sign In
or continue with e-mail and password
Forgot password?
Don't have an account?
Join Canary Wharfian
or continue with e-mail and password
By signing up, you agree to our Terms & Conditions and Privacy Policy.

Lead Software Engineer - Agentic AI

ExperiencedNo visa sponsorship
J.P. Morgan logo

at J.P. Morgan

Bulge Bracket Investment Banks

Posted 2 days ago

No clicks

**Lead Software Engineer - Agentic AI** Lead, design, and deliver resilient cloud-native, AI-powered solutions on AWS, driving innovation at JPMorganChase. Develop, deploy, and maintain microservices-based applications using Python, Flask, Django, and modern AI frameworks (LangChain, LangGraph, AutoGen). Leverage AWS services (ECS, EKS, Lambda, RDS, S3, API Gateway) and Terraform for infrastructure-as-code. Build agentic AI applications enabling autonomous reasoning and tool-use capabilities. Improve operational stability and adopt AI-assisted engineering practices. Lead communities and drive technology awareness. Proven experience (5+ years) in software engineering, AI, and AWS, with strong soft skills and problem-solving abilities. AWS certifications a plus.

Compensation
Not specified USD

Currency: $ (USD)

City
Jersey City
Country
United States

Full Job Description

Location: Jersey City, NJ, United States

 

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorganChase with in Enterprise Technology Cloud Foundational Services, you are an integral part of an agile team that works to enhance, build, and deliver trusted, market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for delivering critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.

 

Job Responsibilities

  • Execute creative software solutions, design, development, and technical troubleshooting, thinking beyond routine or conventional approaches to build solutions or break down technical problems.
  • Deliver end-to-end solutions in the form of cloud-native, microservices-based applications, leveraging the latest technologies and best industry practices.
  • Design, develop, and deploy resilient, fault-tolerant applications on AWS, leveraging services such as ECS, EKS, Lambda, RDS, S3, and API Gateway to ensure high availability and operational excellence.
  • Provision, manage, and maintain cloud infrastructure using Terraform, enforcing infrastructure-as-code best practices, reusable module design, and consistent environment management across development, staging, and production.
  • Architect and build agentic AI applications using modern frameworks (e.g., LangChain, LangGraph, AutoGen, CrewAI, or AWS Bedrock Agents), enabling autonomous, multi-step reasoning and tool-use capabilities within production-grade systems.
  • Identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
  • Lead communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies.
  • Promptly investigate and resolve issues, ensuring they do not resurface.
  • Design and build scalable, secure, and reliable solutions by leveraging modern architectural patterns that ensure zero-downtime releases and optimize data performance.

 

Required Qualifications, Capabilities, and Skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience 
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
  • Proficiency in back-end technologies (e.g., Python, Flask, Django) with experience building microservices-based applications; for full-stack roles, proficiency also includes front-end technologies (e.g., HTML, CSS, JavaScript, TypeScript, React, Angular).
  • Strong hands-on experience developing and deploying resilient applications on AWS, including deep familiarity with core AWS services, high-availability design patterns, disaster recovery strategies, and AWS Well-Architected Framework principles.
  • Strong understanding and hands-on experience in cloud infrastructure provisioning using Terraform, including writing modular, reusable infrastructure-as-code, managing remote state, and integrating Terraform into CI/CD pipelines.
  • Hands-on experience building agentic AI applications using one or more frameworks (e.g., LangChain, LangGraph, AutoGen, CrewAI, AWS Bedrock Agents), including designing multi-agent workflows, tool integrations, memory management, and orchestration patterns.
  • Experience working with cloud platforms (e.g., AWS, Azure, GCP), distributed systems, and web technologies, including RESTful APIs and web services, WebSockets, and JSON.
  • Experience with agile development methodologies (e.g., Scrum) and an understanding of the software development life cycle..
  • Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
  • Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.).

 

Preferred Qualifications, Capabilities, and Skills

  • Strong soft skills, including presentation, negotiation, mentoring, and stakeholder management.
  • Strong problem-solving, analytical, and communication skills.
  • Ability to drive broader impact by sharing and contributing best practices.
  • Experience in the banking domain.
  • AWS certification (e.g., AWS Certified Solutions Architect Associate/Professional, AWS Certified DevOps Engineer, or AWS Certified Machine Learning Specialty).
  • Experience with AWS CDK or CloudFormation as complementary infrastructure tooling alongside Terraform.
  • Familiarity with LLM evaluation frameworks, prompt engineering, and responsible AI practices in the context of agentic system design.

 

Lead design and delivery of resilient cloud-native, AI-powered AWS solutions, driving innovation across JPMorganChase technology.

Lead Software Engineer - Agentic AI

Compensation

Not specified USD

City: Jersey City

Country: United States

J.P. Morgan logo
Bulge Bracket Investment Banks

2 days ago

No clicks

at J.P. Morgan

ExperiencedNo visa sponsorship

**Lead Software Engineer - Agentic AI** Lead, design, and deliver resilient cloud-native, AI-powered solutions on AWS, driving innovation at JPMorganChase. Develop, deploy, and maintain microservices-based applications using Python, Flask, Django, and modern AI frameworks (LangChain, LangGraph, AutoGen). Leverage AWS services (ECS, EKS, Lambda, RDS, S3, API Gateway) and Terraform for infrastructure-as-code. Build agentic AI applications enabling autonomous reasoning and tool-use capabilities. Improve operational stability and adopt AI-assisted engineering practices. Lead communities and drive technology awareness. Proven experience (5+ years) in software engineering, AI, and AWS, with strong soft skills and problem-solving abilities. AWS certifications a plus.

Full Job Description

Location: Jersey City, NJ, United States

 

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorganChase with in Enterprise Technology Cloud Foundational Services, you are an integral part of an agile team that works to enhance, build, and deliver trusted, market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for delivering critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.

 

Job Responsibilities

  • Execute creative software solutions, design, development, and technical troubleshooting, thinking beyond routine or conventional approaches to build solutions or break down technical problems.
  • Deliver end-to-end solutions in the form of cloud-native, microservices-based applications, leveraging the latest technologies and best industry practices.
  • Design, develop, and deploy resilient, fault-tolerant applications on AWS, leveraging services such as ECS, EKS, Lambda, RDS, S3, and API Gateway to ensure high availability and operational excellence.
  • Provision, manage, and maintain cloud infrastructure using Terraform, enforcing infrastructure-as-code best practices, reusable module design, and consistent environment management across development, staging, and production.
  • Architect and build agentic AI applications using modern frameworks (e.g., LangChain, LangGraph, AutoGen, CrewAI, or AWS Bedrock Agents), enabling autonomous, multi-step reasoning and tool-use capabilities within production-grade systems.
  • Identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
  • Lead communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies.
  • Promptly investigate and resolve issues, ensuring they do not resurface.
  • Design and build scalable, secure, and reliable solutions by leveraging modern architectural patterns that ensure zero-downtime releases and optimize data performance.

 

Required Qualifications, Capabilities, and Skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience 
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
  • Proficiency in back-end technologies (e.g., Python, Flask, Django) with experience building microservices-based applications; for full-stack roles, proficiency also includes front-end technologies (e.g., HTML, CSS, JavaScript, TypeScript, React, Angular).
  • Strong hands-on experience developing and deploying resilient applications on AWS, including deep familiarity with core AWS services, high-availability design patterns, disaster recovery strategies, and AWS Well-Architected Framework principles.
  • Strong understanding and hands-on experience in cloud infrastructure provisioning using Terraform, including writing modular, reusable infrastructure-as-code, managing remote state, and integrating Terraform into CI/CD pipelines.
  • Hands-on experience building agentic AI applications using one or more frameworks (e.g., LangChain, LangGraph, AutoGen, CrewAI, AWS Bedrock Agents), including designing multi-agent workflows, tool integrations, memory management, and orchestration patterns.
  • Experience working with cloud platforms (e.g., AWS, Azure, GCP), distributed systems, and web technologies, including RESTful APIs and web services, WebSockets, and JSON.
  • Experience with agile development methodologies (e.g., Scrum) and an understanding of the software development life cycle..
  • Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
  • Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.).

 

Preferred Qualifications, Capabilities, and Skills

  • Strong soft skills, including presentation, negotiation, mentoring, and stakeholder management.
  • Strong problem-solving, analytical, and communication skills.
  • Ability to drive broader impact by sharing and contributing best practices.
  • Experience in the banking domain.
  • AWS certification (e.g., AWS Certified Solutions Architect Associate/Professional, AWS Certified DevOps Engineer, or AWS Certified Machine Learning Specialty).
  • Experience with AWS CDK or CloudFormation as complementary infrastructure tooling alongside Terraform.
  • Familiarity with LLM evaluation frameworks, prompt engineering, and responsible AI practices in the context of agentic system design.

 

Lead design and delivery of resilient cloud-native, AI-powered AWS solutions, driving innovation across JPMorganChase technology.