
at J.P. Morgan
Bulge Bracket Investment BanksPosted 13 days ago
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**Software Engineer III - Python, AI ML, Cloud** - **Design & Deliver Secure, Scalable AI ML Products** as part of an agile team in Asset & Wealth Management, JPMorgan Chase. - **Key Responsibilities:** Build and operate sophisticated LLM-driven applications, collaborate with cross-functional teams (Data Science, Cybersecurity, DevOps), optimize ML products, and stay current with AI advancements. - **Required Skills & Experience:** - Proven software engineering experience (3+ years) and hands-on expertise in Python, AI ML, Azure/AWS, Kubernetes, Airflow. - Proficient in all SDLC aspects and cloud-native architectures. - Experience with Terraform, IaaC, and real-time applications performance tuning. - Familiarity with responsible AI use in workflows and safe handling of data. - **Preferred Skills:** Experience with financial data, AI agentic frameworks, and advanced LLM fine-tuning techniques.
- Compensation
- Not specified
- City
- Bengaluru
- Country
- India
Currency: Not specified
Full Job Description
Location: Bengaluru, Karnataka, India
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 firms 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.




