Senior Lead AI Engineer, Software Engineer

JPMorgan Chase

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Wilmington, DE
Posted: 9 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 $208k

$173k most similar roles pay here $237k

This listing doesn't post a salary. Most similar roles pay $184,756–$230,400.

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 · Senior Lead AI Engineer, Software Engineer

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As an AI Engineer - Sr Lead Software Engineer on the AI/ML Data Platforms team, you will join an agile team focused on building and delivering secure, scalable technology products. You will provide engineering leadership by designing agentic AI platforms and large language model-enabled services for enterprise use cases. Your daily responsibilities include developing production-grade code, leading code reviews, and making architectural decisions to improve system quality and observability. You will build cloud-native services on AWS using containers and serverless architectures while implementing retrieval-augmented generation solutions involving embeddings and semantic search. Key technical requirements include proficiency in Python, PyTorch, or TensorFlow, along with expertise in vector storage systems, MLOps practices, and CI/CD pipelines. You will also drive the adoption of AI-assisted engineering practices to enhance code quality and delivery speed within a regulated environment.

Skills

Python PyTorch TensorFlow AWS Azure LLM RAG MLOps CI/CD Microservices Serverless Prompt Engineering Agentic AI SDLC Monitoring Automated Testing

What you'll do

Build and operate production-grade LLM applications featuring agentic patterns and tool integrations for enterprise use cases.
Design and deliver cloud-native services on AWS using containers and serverless architectures with a focus on scalability.
Implement retrieval-augmented generation (RAG) solutions including embeddings, semantic search, and context engineering to improve output quality.
Drive architecture and design decisions that influence product functionality, technical operations, and software development life cycle practices.
Develop secure production code while leading code reviews to ensure high standards of quality and maintainability.
Lead the adoption and governance of AI-assisted engineering practices to improve delivery speed and operational outcomes.
Provide technical guidance and leadership to resolve complex problems and align priorities across multiple teams.

What we're looking for

Formal training or certification on software engineering concepts and 5+ years of applied experience.
Strong Python engineering skills with experience using PyTorch or TensorFlow.
Expertise in vector storage systems and designing memory for agents.
Experience developing long-running autonomous agents using tools, skills, and human-in-the-loop components.
Proven experience deploying LLM-backed services to production as APIs and microservices.
Deep MLOps experience including CI/CD, monitoring, incident response, and model governance.
Cloud-native AI deployment experience on AWS or Azure with cost and performance optimization.
Demonstrated experience designing and leading the adoption of agentic AI-enabled development practices across teams.

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