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AI/ML Lead Software Engineer

ExperiencedNo visa sponsorship
J.P. Morgan logo

at J.P. Morgan

Bulge Bracket Investment Banks

Posted 2 months ago

No clicks

As an AI/ML Lead Software Engineer on Client Onboarding Technology at JPMorgan Chase, you will lead the design and delivery of multi-agent and Agentic Analytics systems, driving deployment of generative and classical ML solutions. You will be hands-on in Python development, building scalable data pipelines and end-to-end AWS-deployed ML workflows, and using multi-agent orchestration tools like LangGraph or JPMC’s SmartSDK. The role includes mentoring engineers, ensuring production quality and operational stability, and partnering with data science, product, and business stakeholders to deliver impactful solutions.

Compensation
Not specified

Currency: Not specified

City
Glasgow
Country
United Kingdom

Full Job Description

Location: GLASGOW, LANARKSHIRE, United Kingdom

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, within Client Onboarding Technology at JPMorganChase, you will lead a specialized technical area, driving impact across teams, technologies, and projects. In this role, you will leverage your deep knowledge of software engineering, multi-agent system design and leadership to spearhead the delivery of complex and groundbreaking initiatives that will transform Business analytics.

 

You will be responsible for hands-on development, and mentoring  a team of Software Engineers, focusing on best practices in ML engineering and Agentic Analytics, with the goal of elevating team performance to produce high-quality, scalable systems. You will also engage and partner with data science, product and business teams to deliver end-to-end solutions that will drive value for the Client Onboarding business.

 

Responsibilities:

  • Lead the deployment and scaling of advanced generative AI, Agentic AI and classical ML solutions
  • Develop multi-agent systems that provide capabilities for orchestration, agent-to-agent communication, memory, telemetry, guardrails, etc.
  • Conduct and guide research on context and prompt engineering techniques to improve the performance of prompt-based models, exploring and utilizing Agentic AI libraries like JPMC’s SmartSDK and LangGraph.
  • Develop and maintain tools and frameworks for prompt-based agent evaluation, monitoring and optimization to ensure high reliability at enterprise scale.
  • Build and maintain data pipelines and data processing workflows for scalable and efficient consumption of data.
  • Develop secure, high-quality production code, and provide code reviews. 
  • Foster productive partnership with Data Science, Product and Business teams to identify requirements and develop solutions to meet business needs.
  • Communicate effectively with both technical and non-technical stakeholders, including senior leadership.
  • Provide technical leadership, mentorship and guidance to junior engineers, promoting a culture of excellence, continuous learning, and professional growth.

 

Required qualifications, capabilities and skills:

  • Bachelor’s degree or Master’s in Computer Science, Engineering, Data Science, or related field
  • Applied experience in Machine Learning Engineering.
  • Strong proficiency in Python and experience deploying end-to-end pipelines on AWS.
  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Hands-on experience using LangGraph or JPMC’s SmartSDK for multi-agent orchestration.
  • Experience with AWS and Infrastructure-as-code tools like Terraform.

 

Preferred Qualifications:

  • Strategic thinker with the ability to drive technical vision for business impact.
  • Demonstrated leadership working effectively with engineers, data scientists, and ML practitioners.
  • Familiarity with MLOps practices, including CI/CD for ML, model monitoring, automated deployment, and ML pipelines.
  • Experience with Agentic telemetry and evaluation services.
  • Demonstrated hands-on experience building and maintaining user interfaces
Lead Software Engineer developing Agentic Analytics and Business Intelligence solutions

AI/ML Lead Software Engineer

Compensation

Not specified

City: Glasgow

Country: United Kingdom

J.P. Morgan logo
Bulge Bracket Investment Banks

2 months ago

No clicks

at J.P. Morgan

ExperiencedNo visa sponsorship

As an AI/ML Lead Software Engineer on Client Onboarding Technology at JPMorgan Chase, you will lead the design and delivery of multi-agent and Agentic Analytics systems, driving deployment of generative and classical ML solutions. You will be hands-on in Python development, building scalable data pipelines and end-to-end AWS-deployed ML workflows, and using multi-agent orchestration tools like LangGraph or JPMC’s SmartSDK. The role includes mentoring engineers, ensuring production quality and operational stability, and partnering with data science, product, and business stakeholders to deliver impactful solutions.

Full Job Description

Location: GLASGOW, LANARKSHIRE, United Kingdom

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, within Client Onboarding Technology at JPMorganChase, you will lead a specialized technical area, driving impact across teams, technologies, and projects. In this role, you will leverage your deep knowledge of software engineering, multi-agent system design and leadership to spearhead the delivery of complex and groundbreaking initiatives that will transform Business analytics.

 

You will be responsible for hands-on development, and mentoring  a team of Software Engineers, focusing on best practices in ML engineering and Agentic Analytics, with the goal of elevating team performance to produce high-quality, scalable systems. You will also engage and partner with data science, product and business teams to deliver end-to-end solutions that will drive value for the Client Onboarding business.

 

Responsibilities:

  • Lead the deployment and scaling of advanced generative AI, Agentic AI and classical ML solutions
  • Develop multi-agent systems that provide capabilities for orchestration, agent-to-agent communication, memory, telemetry, guardrails, etc.
  • Conduct and guide research on context and prompt engineering techniques to improve the performance of prompt-based models, exploring and utilizing Agentic AI libraries like JPMC’s SmartSDK and LangGraph.
  • Develop and maintain tools and frameworks for prompt-based agent evaluation, monitoring and optimization to ensure high reliability at enterprise scale.
  • Build and maintain data pipelines and data processing workflows for scalable and efficient consumption of data.
  • Develop secure, high-quality production code, and provide code reviews. 
  • Foster productive partnership with Data Science, Product and Business teams to identify requirements and develop solutions to meet business needs.
  • Communicate effectively with both technical and non-technical stakeholders, including senior leadership.
  • Provide technical leadership, mentorship and guidance to junior engineers, promoting a culture of excellence, continuous learning, and professional growth.

 

Required qualifications, capabilities and skills:

  • Bachelor’s degree or Master’s in Computer Science, Engineering, Data Science, or related field
  • Applied experience in Machine Learning Engineering.
  • Strong proficiency in Python and experience deploying end-to-end pipelines on AWS.
  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Hands-on experience using LangGraph or JPMC’s SmartSDK for multi-agent orchestration.
  • Experience with AWS and Infrastructure-as-code tools like Terraform.

 

Preferred Qualifications:

  • Strategic thinker with the ability to drive technical vision for business impact.
  • Demonstrated leadership working effectively with engineers, data scientists, and ML practitioners.
  • Familiarity with MLOps practices, including CI/CD for ML, model monitoring, automated deployment, and ML pipelines.
  • Experience with Agentic telemetry and evaluation services.
  • Demonstrated hands-on experience building and maintaining user interfaces
Lead Software Engineer developing Agentic Analytics and Business Intelligence solutions