Senior Lead Software Engineer - Python & AI

Salary: $64,000 - 104,000 per year Requirements:

• We require formal training or certification in software engineering concepts, along with 5+ years of applied experience.
• We need hands-on experience developing LLM-based applications, including agentic architectures, RAG pipelines, prompt engineering, and evaluation frameworks.
• We look for strong software engineering fundamentals across distributed systems, event-driven architectures, API design, testing practices, and cloud platforms such as AWS, EKS, or ECS.
• We require advanced proficiency with AI-assisted development tools such as Claude Code, GitHub Copilot, or Cursor as part of the daily workflow.
• We need strong Python development experience in production environments.
• We expect proven ability to run and troubleshoot complex systems with full ownership of delivered work.
• We look for clear communication skills and the ability to explain technical trade-offs to engineers and business partners.
• We require demonstrated experience leading effective use of enterprise-approved AI-assisted software development tools, including coding, code review, test acceleration, and troubleshooting.
• We need the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• We require strong understanding of responsible AI practices in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and resiliency and security expectations.
• We value experience coaching senior engineers or leads on compliant AI usage patterns and control measures.
• We require a background in Computer Science, Computer Engineering, Mathematics, or another related technical field.
• We prefer experience with legacy systems, mainframe technologies such as COBOL, JCL, and DB2, or large-scale migration programs.
• We prefer familiarity with workflow orchestration tools such as Temporal or Airflow, as well as event sourcing and CDC patterns.
• We prefer experience building code analysis, translation, or verification tooling.
• We prefer experience with Kafka, PostgreSQL, and container orchestration such as Kubernetes or EKS.
• We prefer a background in financial services, including wealth management, brokerage, or capital markets processing.

• We build and operate the specification generation pipeline by ingesting artifacts such as COBOL source, JCL, job schedules, DB2 schemas, and SME knowledge, then chunking and retrieving information to produce structured calculation and workflow specifications.
• We develop agentic workflows that translate legacy logic into target-state Kotlin or JVM code, including orchestration layers, tool-use patterns, and guardrails that protect calculation accuracy.
• We create evaluation and verification infrastructure, including automated harnesses, parity tests, regression suites, and confidence scoring to support production cutover decisions.
• We contribute to the standard calculation runtime so migrated calculations execute in a deterministic, immutable, and auditable environment.
• We partner closely with domain SMEs across Credit, Money Market & Mutual Funds, Statements & Tax, and IBOR to validate outputs, refine prompting strategies, and resolve specification gaps.
• We extend ETL and CDC pipelines for agent workflows, including event sourcing and dependency mapping across upstream and downstream systems.
• We operate AI systems in production by owning LLMOps activities such as deployment, monitoring, cost control, latency tuning, token budgeting, and incident response.
• We iterate quickly through build-measure-learn cycles, prototype rapidly, instrument solutions, and use data to guide model, architecture, and prompt decisions.
• We build reusable tooling and infrastructure, including libraries, evaluation harnesses, prompt templates, and orchestration patterns that scale AI capabilities across core processing domains.
• We drive adoption and governance of approved AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes while maintaining measurable validation standards.
• We apply approved SDLC toolchain capabilities to increase the value delivered by automation at scale.

• AI
• Airflow
• API
• AWS
• Claude Code
• Cloud
• COBOL
• Copilot
• Cursor
• ETL
• GitHub
• Support
• JVM
• Kafka
• Kotlin
• Kubernetes
• LLM
• Mobile
• PostgreSQL
• Python
• RAG
• Security

More:

We are JPMorganChase, one of the oldest financial institutions, serving consumers, small businesses, and major corporate, institutional, and government clients through the J.P. Morgan and Chase brands. Our team within Consumer and Community Banking supports wealth management technology and builds innovative, secure, stable, and scalable products for a global customer base. We offer a competitive total rewards package and a broad range of benefits, including health coverage, wellness centers, retirement savings, backup childcare, tuition support, mental health resources, and financial coaching, depending on eligibility. We are deeply committed to diversity, inclusion, and equal opportunity. Our Consumer & Community Banking group powers award-winning tools and services across banking, lending, mortgages, credit cards, payments, auto finance, and investment advice, while advancing next-generation digital experiences and mobile banking technology.

last updated 33 week of 2026