Senior Lead Software Engineer- Python Distributed Development and AI Modernization

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products within the Consumer and Community Bank - Wealth Management Technology at JPMorganChase.

About the role

As a Senior Lead Software Engineer specializing in Python Distributed Development and AI Modernization, you will design, build, and ship agentic systems that ingest decades of mainframe logic and produce verified, production-ready modern services. You will work directly alongside domain subject-matter experts (SMEs) to transform legacy COBOL, JCL, DB2, and batch schedules into structured specifications, then drive those specs through agent-accelerated delivery into the target platform. This role requires a builder-first mindset: you will architect multi-agent orchestration, debug prompt chains against production edge cases, and ensure AI outputs are reliable at enterprise scale.

Responsibilities

• Build and operate the spec generation pipeline — Implement artifact ingestion (COBOL source, JCL, job schedules, DB2 schemas, SME-captured knowledge), chunking strategies, and RAG pipelines that produce structured calculation and workflow specifications validated by domain experts.
• Develop agentic workflows for code translation and migration — Design, implement, and iterate on multi-agent systems that translate legacy logic into target-state code (Kotlin/JVM). Build orchestration layers, tool-use patterns, and guardrails to ensure output correctness for financial calculations.
• Build evaluation and verification infrastructure — Create automated test harnesses that compare migrated calculation outputs against legacy results. Implement parity testing frameworks, regression suites, and confidence scoring to gate production cutover decisions.
• Contribute to the standard calculation runtime — Help build and extend the target platform that migrated calculations deploy into, ensuring deterministic, immutable, auditable execution.
• Partner with domain SMEs — Embed with mainframe subject-matter experts across Credit, Money Market & Mutual Funds, Statements & Tax, and IBOR to validate agent outputs, refine prompt strategies, and close knowledge gaps in specifications.
• Extend ETL and CDC pipelines for agent workflows — Build and integrate event sourcing, CDC (change data capture), and data pipelines that support end-to-end migrated workflows, including upstream/downstream dependency mapping.
• Operate AI systems in production — Own LLMOps for the toolchain: deployment, monitoring, cost management, latency optimization, token budget management, and incident response. Ensure reliability and compliance for 24/7 operation.
• Iterate rapidly and ship continuously — Work in tight build-measure-learn cycles. Prototype quickly, instrument everything, and make data-driven decisions about agent architectures, model selection, and prompt strategies.
• Contribute to shared tooling and infrastructure — Build reusable libraries, evaluation harnesses, prompt templates, and orchestration patterns that scale AI capabilities across all four core processing domains.
• Drive adoption and governance of approved AI-assisted engineering practices — Improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis) while establishing measurable validation standards (secure coding, peer review, automated testing). Promote reuse of proven patterns and automation within the SDLC/TLM toolchain.
• Apply knowledge of tools within the Software Development Life Cycle toolchain — Use approved AI-assisted development and automation capabilities to improve the value realized by automation at scale.

Requirements

• Formal training or certification on software engineering concepts and 5+ years of applied experience.
• Hands-on experience building LLM-based applications — agentic architectures, RAG pipelines, prompt engineering, and evaluation frameworks.
• Strong software engineering fundamentals: distributed systems, event-driven architectures, API design, testing practices, and cloud platforms (AWS/EKS/ECS).
• Expert proficiency with AI-assisted development tools (Claude Code, GitHub Copilot, Cursor) as core daily workflow.
• Strong experience with Python development in production environments.
• Demonstrated ability to operate and debug complex systems — you own what you ship.
• Clear communicator who can articulate technical trade-offs to both engineers and business stakeholders.
• Demonstrated experience leading effective use of enterprise-authorized 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 senior engineers/leads on compliant usage patterns and controls.
• Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field.

Preferred Qualifications

• Experience with legacy systems, mainframe technologies (COBOL, JCL, DB2), or large-scale migration programs.
• Familiarity with workflow orchestration (Temporal, Airflow) and event sourcing/CDC patterns.
• Experience building code analysis, translation, or verification tooling.
• Experience with Kafka, PostgreSQL, and container orchestration (Kubernetes/EKS).
• Background in financial services — wealth management, brokerage, or capital markets processing.

Benefits

• Competitive total rewards package including base salary, commission-based pay, and discretionary incentive compensation (cash and/or forfeitable equity).
• Comprehensive health care coverage, on-site health and wellness centers.
• Retirement savings plan, backup childcare, tuition reimbursement.
• Mental health support, financial coaching, and more.