Lead AI Platform Engineer

Aumni; Palo Alto (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorganChase in Palo Alto seeks a Lead Software Engineer to architect and deliver scalable, enterprise-grade AI platforms leveraging LLMs and agentic workflows. You will design cloud-native solutions on AWS, build production-grade AI services, and drive reliability, observability, and cost controls across teams.

The role emphasizes hands-on delivery, collaboration with product and engineering, and mentoring of senior engineers to push technology directions while ensuring secure, compliant AI

Qualifications

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Experience architecting and shipping production large language model applications, including agentic workflows and tool integration patterns.
• Strong software engineering fundamentals with ability to deliver cloud-native services using containers and serverless designs on AWS.
• Proficiency designing distributed systems with asynchronous workflows, durable messaging, and scalable data access patterns.
• Experience building retrieval-augmented generation solutions (embeddings, semantic search, grounding) and managing prompt lifecycle/versioning.
• Demonstrated ability to implement evaluation and monitoring approaches for model quality, reliability, and safe behavior over time.
• Strong API design skills, including secure integration patterns and reusable platform capability development.
• Proven technical leadership skills, including mentoring, driving architecture decisions, and influencing cross-functional stakeholders.
• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.

Responsibilities

• Lead the architecture and hands-on delivery of scalable, reliable agentic AI platforms for enterprise workflows.
• Design and build production-grade AI systems including agents, skills, memory patterns, guardrails, and tool-use orchestration.
• Architect retrieval and context-engineering approaches including embeddings, semantic search, grounding, summarization, and prompt/version management.
• Engineer cloud-native AI services on AWS using containers and serverless patterns, event-driven messaging, and distributed data stores.
• Optimize platform performance across latency, throughput, scalability, caching, context efficiency, and cost controls.
• Build well-governed APIs and integrations that connect AI capabilities to enterprise platforms, tools, and business processes.
• Establish evaluation, experimentation, regression testing, and observability frameworks to continuously improve quality and agent behavior.
• Define engineering standards for reliability, security, and safe AI operation across the platform lifecycle.
• Mentor senior engineers and influence engineering direction through code reviews, architecture forums, and cross-team technical leadership.
• Leverages enterprise-authorized AI coding assist tools to improve code quality, delivery speed, and productivity across complex deliverables, while validating outputs through peer review, automated testing, and secure coding standards.
• Applies knowledge of SDLC tools and automation capabilities to improve value realized by automation.

Skills

LLM systems

Agentic AI platforms

AWS cloud

Containers

Serverless

Mentoring

Education

Bachelor's degree in CS or related field

Tools

Kubernetes

Terraform

Git

Observability tools

Job description

JPMorganChase in Palo Alto seeks a Lead Software Engineer to architect and deliver scalable, enterprise-grade AI platforms leveraging LLMs and agentic workflows. You will design cloud-native solutions on AWS, build production-grade AI services, and drive reliability, observability, and cost controls across teams.

The role emphasizes hands-on delivery, collaboration with product and engineering, and mentoring of senior engineers to push technology directions while ensuring secure, compliant AI