Lead Software Engineer - Java/Python, React

Aumni

Bengaluru

On-site

INR 600,000 - 1,200,000

Full time

14 days+

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Job summary

JPMorgan Chase is seeking a Lead Software Engineer in Bengaluru to drive AI-first horizontal engineering for the AIS product line. You will design, build, and ship reusable components, automation, and cross-product accelerators to improve stability and consistency.

You will leverage AI agents across workflows, while ensuring quality and accountability. You will lead a team, establish disciplined AI-enabled workflows, and partner with AIS product teams to shape a governance-driven backlog aligned

Qualifications

  • Formal training or certification on software engineering concepts.
  • Advanced proficiency in Java/Python with system design and deployment experience.
  • Proficiency in automation, CI/CD, and SDLC practices.
  • Strong understanding of agile methodologies, security, and AI-assisted tooling.

Responsibilities

  • Design and deliver secure, high-quality production code for AIS-wide capabilities and reusable components.
  • Lead AI-first engineering delivery using AI agents across analysis, coding, testing, and documentation.
  • Establish human-plus-AI workflows with prompts, reviews, and validation checkpoints.
  • Drive standardization across AIS products by creating reusable libraries and reducing duplication.
  • Mentor engineers, conduct code reviews, and provide technical oversight.

Skills

Java/Python
System design
CI/CD
Automation
SDLC
Agile
AI-assisted tools
Security
React
Cloud-native

Education

Software engineering training

Job description

Join a dynamic team driving innovation in AI-first engineering. Unlock your potential and shape the future of application integration and streaming.

As a Lead Software Engineer at JPMorgan Chase within the Horizontal Engineering team, you will deliver AI-first horizontal engineering capabilities for the AIS product line. You will design, build, and ship reusable components, automation, and cross-product accelerators to improve operational stability and engineering consistency. You will leverage AI agents across multiple engineering workflows, always maintaining accountability for quality and outcomes. You will play a key role in shaping technical solutions and driving standardization across AIS products.

Job responsibilities
  • Design and deliver secure, high-quality production code for reusable AIS-wide capabilities, including shared components, automation, APIs, SDKs, infrastructure-as-code, and cross-product engineering patterns.
  • Execute creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems.
  • Lead AI-first engineering delivery by using AI agents across analysis, code generation, testing, documentation, controls evidence, configuration management, reusable component development, and operational diagnostics.
  • Establish disciplined human-plus-AI workflows, including context curation, prompt and skills management, review checkpoints, approval gates, escalation paths, auditability, and output validation.
  • Drive standardization across AIS products by reducing duplicated engineering work, creating reusable libraries and modules, improving observability, and automating recurring operational or engineering issues.
  • Identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.
  • Provide senior engineering judgment through design challenge, code review, debugging, quality oversight, mentoring, and coaching of engineers working in an AI-enabled delivery model.
  • Partner with AIS product teams, architecture, and engineering stakeholders to shape and deliver a governed backlog of cross-product work aligned to the AIS strategic Book of Work.
  • Lead communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies, AI-first delivery, and engineering standardization.
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
  • 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 5+ years applied experience
  • Advanced proficiency in Java/Python, with strong experience across system design, application development, testing, deployment, automation, CI/CD, infrastructure-as-code, and modern SDLC practices.
  • Proficiency in automation and continuous delivery methods.
  • Proficient in all aspects of the Software Development Life Cycle.
  • Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
  • Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, platform engineering, or controls engineering).
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
  • Experience with React for building modern, responsive front-end applications
  • Practical cloud-native experience.
Preferred qualifications, capabilities and skills
  • Experience with cross-product engineering, horizontal capabilities, reusable platforms, shared services, or engineering standardization across multiple product lines.
  • Experience with data lakes, chaos engineering, cloud native development or compliance engineering in regulated financial services.
  • Experience building AI agents, agent-assisted engineering workflows, automated testing, documentation generation, anomaly detection, or developer productivity tooling.
  • Experience with multi-cloud or cloud-portable platform patterns across private cloud, AWS, Azure, or GCP.

Lead AI-first engineering delivery, designing and building reusable solutions to accelerate AIS product development.

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