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JPMorganChase

Lead Software Engineer - Python, Data, Cloud, AIML

Posted An Hour Ago
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Hybrid
London, Greater London, England, GBR
Entry level
Hybrid
London, Greater London, England, GBR
Entry level
Lead a hands-on software engineering role building secure, scalable cloud-native data and AI/ML platforms. Responsibilities include Python development, system design, microservices, distributed systems, data engineering, backend engineering, cloud infrastructure, DevOps, MLOps, production troubleshooting, and architecture. The role involves AWS data services, modern big-data technologies, containerized applications, and collaboration with data scientists and stakeholders. Experience with Kubernetes, LLMs, RAG, knowledge graphs, OpenSearch, and vector databases is preferred.
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We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Bank's Markets Research Technology team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. You will work on challenging Cloud-native data, backend engineering and AIML engineering, helping us industrialize AI/ML models at Production scale. This role is a technical hands-on Engineering role. Experience with data science/ML modeling is advantageous but not essential to this role.

Job responsibilities 

  • Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems

  • Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems

  • Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development

  • Builds engineering stack required for Data and AIML products, including data engineering, backend engineering, Cloud infra DevOps and MLOps

  • Designs and implements data engineering solutions, leveraging modern big data technologies   

  • Contributes to software engineering communities of practice and events that explore new and emerging technologies

  • Embraces a passion for learning, problem-solving, creative thinking and a can-do attitude.

 

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and proficient applied experience

  • Hands-on practical experience in system design, application development, testing, and operational stability

  • Proficient in coding in one or more languages- Python

  • Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages

  • Overall knowledge of the Software Development Life Cycle

  • Proven track record in system design, architecting and developing microservices, distributed systems and data-intensive applications

  • Experience with Cloud services, Infrastructure as Code, containerized application development, big data and modern data engineering technologies        

  • Practical experience developing Production-scale Cloud-native data engineering solutions in commercial environments   

  • Familiarity with Cloud Data engineering services (e.g., ETL, Glue, S3, Athena) and MLOps stack   

  • Ability to convey design choices and results clearly and communicate effectively to stakeholders of various backgrounds 

 

 Preferred qualifications, capabilities, and skills

  • Experience with data, AWS and AIML engineering in commercial settings, preferably in financial sector

  • Experience working on recommendation systems, LLM applications or other AI/ML systems 

  • Practical experience with Kubernetes, EKS, Docker, MLOps

  • Prior exposure to LLMs, RAG, Knowledge Graph Technologies, OpenSearch and vector databases  

  • Prior experience collaborating with data scientists 

 
About UsJ.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
  
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.
About the TeamJ.P. Morgan’s Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. 

JPMorganChase London, England Office

25 Bank Street, Canary Wharf, London, United Kingdom, E14 5JP

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