AI Engineer, Lead Software Engineer

JPMorgan Chase

Confirmed live yesterday Trusted

Quick summary

Work type: On-site
Location: Jersey City, NJ
Posted: 79 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $205k

$180k most similar roles pay here $230k

This listing doesn't post a salary. Most similar roles pay $185,500–$223,750.

Based on 240 similar postings.

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About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1117 open roles on FindRole.

Listed pay typically runs $186,160–$215,000 across 7 roles with salary data.

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At a glance

TL;DR · AI Engineer, Lead Software Engineer

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As an AI Engineer - Lead Software Engineer within Enterprise Technology, you will lead the architecture and hands-on implementation of scalable large language model systems and agentic AI platforms for enterprise use cases. You will design cloud-native solutions, establish evaluation and observability standards, and drive technical decisions to improve reliability, cost, and developer velocity. Your daily work involves building production-grade AI systems including agents, memory patterns, guardrails, and tool-use orchestration while architecting retrieval-augmented generation approaches like embeddings and semantic search. You will engineer services on AWS using containers, serverless patterns, and distributed data stores to connect AI capabilities to business processes. Required skills include experience with agentic workflows, prompt management, and API design. You must possess strong leadership to mentor engineers and manage the lifecycle of secure, high-availability systems in a regulated environment.

Skills

LLM Agentic AI AWS Kubernetes Serverless Semantic Search API Design Distributed Systems Observability

What you'll do

Lead the architecture and hands-on delivery of scalable agentic AI platforms for enterprise workflows.
Design production-grade AI systems including agents, memory patterns, guardrails, and tool-use orchestration.
Architect retrieval and context-engineering solutions involving embeddings, semantic search, and prompt management.
Engineer cloud-native AI services on AWS using containers, serverless patterns, and distributed data stores.
Optimize platform performance regarding latency, throughput, scalability, and cost controls.
Build well-governed APIs to connect AI capabilities to enterprise platforms and business processes.
Establish evaluation, regression testing, and observability frameworks to improve model quality and behavior.
Define engineering standards for reliability, security, and safe AI operation across the platform lifecycle.

What we're looking for

Formal training or certification in software engineering concepts and 5+ years of applied experience.
Experience architecting and shipping production large language model applications, including agentic workflows and tool integration patterns.
Strong software engineering fundamentals 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 involving embeddings, semantic search, grounding, and prompt lifecycle management.
Demonstrated ability to implement evaluation and monitoring approaches for model quality, reliability, and safe behavior.
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.