Lead Software Engineer - Python and AI
JPMorgan Chase1 day ago
Bengaluru, IndiaStaff+
Responsibilities
- Design and build production-grade agentic AI systems, including LLM orchestration layers, RAG pipelines, vector databases, and MCP-based tool integrations.
- Develop, review, debug, and maintain secure, high-quality Python software, including code generated or assisted by AI models.
- Architect single-agent and multi-agent systems, author skill files, and write technical RFCs for new AI capabilities.
- Contribute to AWS ECS cloud-native deployments, CI/CD pipelines, and infrastructure modernization.
- Build and iterate on agentic patterns from proof of concept through user acceptance testing and production rollout.
- Translate regulatory operations and business requirements into technical designs and deliver against quarterly commitments.
- Automate recurring operational issues to reduce manual toil and improve platform stability.
- Participate in sprint ceremonies, code reviews, architecture discussions, and technical mentoring.
- Build and support an internal developer productivity accelerator across more than 10 cross-functional teams.
- Lead adoption of enterprise-authorized AI-assisted engineering practices, including AI-assisted code review, refactoring, testing, and troubleshooting.
- Establish validation standards for AI-assisted development, including secure coding, peer review, automated testing, correctness, performance, and security checks.
Requirements
- Formal training or certification in software engineering concepts and at least 5 years of applied experience.
- Hands-on experience with system design, application development, testing, and operational stability.
- Advanced proficiency in Python and strong object-oriented programming fundamentals.
- Proven experience building and deploying LLM-based or agentic AI systems in production.
- Deep understanding of RAG architecture, vector databases, and AI agent frameworks such as LangGraph and MCP.
- Proficiency in automation, CI/CD, DevSecOps, and all phases of the Software Development Life Cycle.
- Practical AWS cloud-native experience, including ECS, Lambda, S3, or equivalent services.
- Advanced understanding of agile methodologies and application resiliency patterns.
- Ability to independently analyze and break down complex technical problems.
- Experience leading the effective use of approved AI-assisted software development tools and validating AI outputs for correctness, performance, and security.
- Understanding of responsible AI use, data sensitivity, secure input and output handling, resiliency, and security expectations.
- Preferred experience with post-trade financial platforms such as Athena, Quartz, or SecDB.
- Preferred knowledge of financial services IT systems, trade reconciliation, and regulatory reporting workflows.
- Preferred experience with AI, ML, vibe coding, agentic development workflows, distributed computing, data modeling, performance engineering, data lineage, data contracts, data governance, ServiceNow, Jira, Confluence API integrations, regression testing, and observability tooling.
Categories
About JPMorgan Chase
JPMorgan Chase provides consumer and commercial banking, payments, credit card, wealth management, and corporate and investment banking services to individuals, businesses, institutions, and governments. The public company (NYSE: JPM) earns revenue from interest, fees, trading, and asset management across operations in more than 100 markets. Headquartered in New York City with roots dating to 1799, it serves retail customers and prominent corporate and government clients through brands including Chase and J.P. Morgan.