Lead Software Engineer
About The Position
Join JPMorganChase’s Corporate Artificial Intelligence and Machine Learning Data Platforms team to build and enhance products supporting the end-to-end machine learning lifecycle. This includes model operations, data development such as processing and annotation, and governance tooling. The role involves collaborating with engineers, system architects, product managers, data scientists, and research partners to deliver reliable, secure, and user-friendly platform services that help teams move machine learning work from ideas to production. The engineer will develop scalable platform capabilities and cloud-native services, improve developer experience, and contribute to model and feature registries, governance workflows, data preparation, annotation, lineage, and auditability. The role also includes implementing controlled and evaluated LLM-powered features, maintaining architecture and design artifacts, using approved AI-assisted development tools responsibly, and improving platform reliability and adoption through operational metrics and user feedback.
Requirements
- Formal training or certification in software engineering concepts and at least 3 years of applied experience.
- Experience building and delivering backend or platform services using modern architecture patterns, including microservices, reactive architectures, or event-driven architectures.
- Experience developing and deploying LLM-powered solutions using prompt design, agent workflows, tool integration, and retrieval techniques.
- Proficiency in at least two modern languages or frameworks such as Python, Java, JavaScript, React, or Node.js.
- Experience building and consuming RESTful APIs, including performance tuning in large-scale applications.
- Experience with cloud platforms and containerization or orchestration tools such as Docker and Kubernetes.
- Experience with relational and non-relational databases such as PostgreSQL, MongoDB, Redis, Elasticsearch, or Cassandra.
- Experience with engineering practices including refactoring, design patterns, automated testing, continuous integration, continuous delivery, and application security.
- Hands-on experience using approved AI-assisted software development tools, with the ability to validate and refine outputs for correctness, performance, and security.
Nice To Haves
- Proficiency in Go or Terraform for automation, tooling development, or platform service implementation.
- Working knowledge of machine learning frameworks such as PyTorch, TensorFlow, Hugging Face, or scikit-learn for model integration and operationalization.
- Exposure to multi-cloud or hybrid cloud architectures and platform portability strategies.
- Experience building governance controls for model lifecycle management, including approvals, policy enforcement, and auditability.
Responsibilities
- Build and enhance platform services for model registries, feature registries, promotion policies, and governance workflows.
- Design and deliver capabilities for data preparation, annotation workflows, lineage, and audit trails.
- Develop cloud-native services and APIs that scale across development and production environments.
- Implement LLM-powered features, including prompt design, agent workflows, tool integration, and retrieval, with strong controls and evaluation practices.
- Produce and maintain architecture and design artifacts, ensuring solutions meet performance, resiliency, and security expectations.
- Use approved AI-assisted development tools responsibly, validating outputs through code review, testing, and secure coding practices.
- Partner with product and engineering stakeholders to prioritize roadmap items and improve platform usability.
- Analyze operational metrics and user feedback to improve reliability, usability, and platform adoption.
- Identify and remediate issues in systems and data, and improve code quality, observability, and maintainability.
Benefits
- Competitive total rewards package, with base salary determined by role, experience, skill set, and location.
- Eligible roles may receive commission-based pay and/or discretionary incentive compensation in 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.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
