JPMorgan Chase & Co.

Software Engineer III - Python, AI ML, Cloud

JPMorgan Chase & Co. · Bengaluru, Karnataka, India

Financial Services · 10,001+ employees

19 h ago
Mid (2-5 yrs) Full-time India
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About the role

Design and deliver scalable, secure LLM-driven applications and ML products within an agile team. Collaborate with Data Science, Cybersecurity, and DevOps to integrate advanced AI technologies into business operations.

What they look for

Python AI/ML Azure AWS Kubernetes Airflow Terraform IaaC Microservices LLM Prompt Optimization Agentic Frameworks Software Development Life Cycle Cloud-Native Architecture Performance Tuning Secure Coding

Requirements

Requires 3+ years of software engineering experience with advanced Python skills and proficiency in Azure or AWS. Must have experience with cloud-native architectures, Kubernetes, and the use of AI-assisted development tools.

Full description

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Software Engineer III at JPMorgan Chase within the Asset & Wealth Management, 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.

Job responsibilities

  • Involves in building and operating highly sophisticated LLM driven applications.
  • Partners directly with other technology teams on LLM projects to advise and assist as needed.
  • Collaborates with Data Science, Cybersecurity to deliver state of the art ML products.
  • Collaborates with Devops engineers to plan and deploy data storage and processing systems,
  • Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
  • Develops secure high-quality production code, and reviews and debugs code written by others.
  • Stays abreast of the latest advancements in AI technologies, and drive their integration into our operations.
  • Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
  • 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.

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 3+ years applied experience
  • Advanced python programming skills. Proven experience in building and operating scalable ML-driven products.
  • Azure and/or AWS Certifications ( Architect, Big Data, AI/ML ) . Hands on experience in Azure and AWS.
  • Proficiency with cloud technologies like Kubernetes, Airflow. Experience working in a highly regulated environment.
  • Proven ability to iterate quickly. Proficient in all aspects of the Software Development Life Cycle.
  • Terraform, IaaC experience. Experience with design & delivery of large scale cloud-native architectures.
  • Experience with microservices performance tuning, performance optimization, real-time applications.
  • Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
  • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.

Preferred qualifications, capabilities, and skills

  • Experience with financial data and data science. Experience in developing AI solutions using agentic frameworks.
  • Experience fine-tuning LLMs with advanced techniques to enhance performance.
  • Experience with prompt optimisation to improve the effectiveness of AI applications.
  • Demonstrated ability to design and implement robust AI application architectures.