Lead Software Engineer - Python/Java AI
Salary not listed • Plano, TX, United States • Full-time
Posted 1mo ago
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Job Location
Plano, TX, United States
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Agent Engineer
About the job
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Software Engineer at JPMorganChase within the Corporate Sector Technology, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Responsibilities
- Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes.
- Establish consistent validation standards and promote reuse of effective patterns across the team.
- Apply knowledge of Software Development Life Cycle tools, including AI-assisted development and automation capabilities, to improve value realized by automation.
- Architect and implement resilient, highly scalable, fault-tolerant, low-latency services and drive target-state architecture.
- Design and deploy services that integrate with enterprise systems, ensuring functional, performance, scalability, security, governance, and auditability requirements are met.
- Lead and mentor the development team in a high-pressured delivery environment, managing multiple deliverables and strengthening stakeholder relationships.
- Collaborate with users, SMEs, architects, DBAs, and system administrators to design solutions, manage enhancements, and resolve issues.
- Build and mature capabilities that execute ML pipelines for fraud detection and risk assessment.
- Support modeling teams in implementation and tooling.
- Production Alize models built by data scientists, including validation readiness and quality controls prior to live usage.
- Design and own reusable ML platform components and establish monitoring/alerting for performance, scalability, availability, and reliability.
- Build agentic AI services to automate and enhance engineering and model-ops workflows.
- Define and implement guardrails and evaluation approaches for agentic AI in production.
Requirements
- Formal training or certification on software engineering concepts and 5+ years applied experience.
- 10+ years of recent hands-on software development experience in large-scale distributed systems, primarily JPython/Java/J2EE and modern Java/Spring Boot microservices.
- 3+ years of experience developing in Linux environments.
- Demonstrated experience leading effective use of approved AI-assisted software development tools.
- 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.
- Strong experience with REST APIs and service-oriented / microservices architecture.
- Strong Kubernetes orchestration experience (building, deploying, and operating production services).
- Messaging expertise with Kafka, MQ, or similar platforms.
- Experience with backend infrastructure patterns (e.g., load balancing, autoscaling).
- Experience with log analytics / observability tools (e.g., ELK, Splunk).
- AI/ML platform exposure (MLOps, feature engineering, model hosting/operationalization; AWS and/or hybrid on-prem + cloud).