Lead Software Engineer - Python - GenAI

Join JPMorganChase in Corporate Technology to lead the design and delivery of secure, scalable AI-enabled services in a high-impact production environment.

Responsibilities

• Architect and implement resilient, highly scalable, fault-tolerant, low-latency services while driving target-state architecture
• Design and deploy services integrated with enterprise systems, meeting functional, performance, scalability, security, governance, and auditability requirements
• Lead and mentor development in a high-pressured delivery environment; manage multiple deliverables across business groups and build strong stakeholder relationships
• Collaborate with line of business users, SMEs, architects, DBAs, and system administrators to design solutions, manage enhancements, and resolve issues
• Build and mature ML pipeline execution capabilities for fraud detection and risk assessment; support modeling teams with implementation and tooling
• Productionalize models created by data scientists, including validation readiness and quality controls prior to live usage
• Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes (AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support)
• Establish consistent validation standards across secure coding, peer review, and automated testing; promote reuse of effective patterns across the team
• Apply tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation, to increase automation value
• Design and own reusable ML platform components (feature-store patterns, delivery pipelines) and implement monitoring and alerting for performance, scalability, availability, and reliability
• Build agentic AI services for engineering and model-ops workflow automation, including tool-using agents, orchestration, state management, and audit-ready traceability
• Define and implement guardrails and evaluation approaches for agentic AI in production, covering quality, safety, latency, and cost

Requirements

• Formal training or certification on software engineering concepts plus 5+ years applied experience; hands-on delivery experience covering system design, application development, testing, and operational stability
• Strong distributed-systems engineering expertise in Python/Java, with strong platform, delivery, and production-operability discipline; recent hands-on work in large-scale distributed systems primarily in Python and modern microservices
• Deep Python experience for AI/ML engineering, automation, model operationalization, and agentic AI services; including tool integration, monitoring, telemetry, and governance
• Strong experience with REST APIs and service-oriented or microservices architecture
• Demonstrated ability to lead effective use of approved AI-assisted software development tools (coding, code review, test acceleration, troubleshooting) and set team expectations for validating AI outputs for correctness, performance, and security
• Strong understanding of responsible AI in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
• Experience developing in Linux environments
• Strong Kubernetes experience building, deploying, and operating production services
• Messaging expertise with Kafka, MQ, or similar platforms
• Backend infrastructure experience such as load balancing and autoscaling; NoSQL experience with Cassandra; log analytics and observability tools such as ELK or Splunk
• Strong SDLC knowledge and agile ways of working, including CI/CD, application resiliency, security, testing, and operational stability; strong communication skills and proven ability to influence senior technology and business stakeholders
• AI/ML platform exposure across MLOps, feature engineering, and model hosting/operationalization; AWS and/or hybrid on-prem plus cloud
• Agentic AI experience building and operating LLM-driven agents with tool integration, monitoring and telemetry, and governance and audit considerations

Technologies

• Python, Java
• AI-assisted software development tools
• REST APIs, microservices
• Linux, Kubernetes
• Kafka, MQ
• Cassandra, ELK, Splunk
• CI/CD
• MLOps, feature engineering
• AWS
• LLM-driven agents

Benefits

• Competitive total rewards package including base salary
• Commission-based pay and/or discretionary incentive compensation (for eligible roles)
• Paid in the form of 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

Preferred Qualifications, Capabilities, and Skills

• AWS Certification(s) and/or working knowledge
• AI Certification(s) and/or working knowledge

About the Team

• Corporate Functions professionals span areas from finance and risk to human resources and marketing
• Corporate teams help ensure businesses, clients, customers, and employees are set up for success