LLM Suite Engineering - Senior Associate Software Engineer III

JPMorgan Chase & Co.
London
5 days ago
Create job alert

This job is brought to you by Jobs/Redefined, the UK's leading over-50s age inclusive jobs board.

Job Description

Join JPMorganChase, a global leader in financial services, as we revolutionize our operations with artificial intelligence and machine learning.

As a Software Engineer III at JPMorgan Chase within the AIML and Data Platforms (AMDP) team, you will be addressing significant challenges in the financial services sector and creating substantial impact. You will have the opportunity to work alongside industry leaders and contribute to pioneering AI/ML capabilities that solidify JPMC's industry leadership. Your crucial role in the LLM Suite within the AMDP team will involve transforming early-stage code into production-ready solutions and developing innovative AI/ML solutions using public cloud architecture. You will also collaborate with cross-functional teams to integrate generative AI into various applications and products.

Job Responsibilities:

  • Develop innovative AI/ML solutions and agentic systems for the LLM Suite platform using Azure, AWS, and AI Agentic frameworks.
  • Integrate with AWS Cloud Services for compute, storage, databases, and security, as well as the Azure ecosystem.
  • Create solutions or tools to provision and monitor infrastructure for LLM and agentic systems.
  • Utilize operational skills to provide impactful recommendations for product, process, or policy improvements.
  • Collaborate with the Product team to design, build, and deliver capabilities in agile sprints.
  • Work with cross-functional teams, including data scientists, software engineers, and designers.
  • Develop and implement state-of-the-art GenAI services leveraging Azure OpenAI models and AWS Bedrock service.

Required Qualifications, Capabilities, and Skills:

  • Formal training or certification on software engineering concepts and proficient applied experience
  • Strong hands-on experience with at least one programming language (Python/Java/Rust)
  • Experience in developing microservices using Python with FastAPI.
  • Commercial experience in both backend and frontend engineering
  • Hands-on experience with AWS Cloud-based applications development, including EC2, ECS, EKS, Lambda, SQS, SNS, RDS Aurora MySQL & Postgres, DynamoDB, EMR, and Kinesis.
  • Strong engineering background in machine learning, deep learning, and neural networks.
  • Experience with containerized stack using Kubernetes or ECS for development, deployment, and configuration.
  • Experience with Single Sign-On/OIDC integration and a deep understanding of OAuth, JWT/JWE/JWS.
  • Solid understanding of backend performance optimization and debugging.
  • Knowledge of AWS SageMaker and data analytics tools.
  • Proficiency in frameworks TensorFlow, PyTorch, or similar.

Preferred Qualifications, Capabilities, and Skills:

  • Familiarity with LangChain, Langgraph, or any Agentic Frameworks is a strong plus.
  • Python engineering experience
  • React

#J-18808-Ljbffr

Related Jobs

View all jobs

Engagement Manager, Enterprise

Sr. AI Lead (Gen AI)

Tech Lead

Sr. AI Lead (Gen AI)

Senior AI Engineer

Software Engineer (Go)

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Machine learning (ML) has become an indispensable force in the modern business world, influencing everything from targeted marketing campaigns to advanced medical diagnostics. As industries integrate predictive algorithms and data-driven decision-making into their core operations, the need for effective leadership in machine learning environments has never been greater. Whether you’re overseeing a small team of data scientists or spearheading an enterprise-scale ML project, your leadership style must accommodate rapid innovation, complex problem-solving, and diverse stakeholder expectations. This guide provides actionable insights into how you can motivate, mentor, and establish achievable goals for your machine learning teams—ensuring they thrive in data-driven environments.

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.