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This listing doesn't post a salary. Most similar roles pay
$195,000–$275,175.
Based on 240 similar postings.
Employer
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
1226 open roles
on FindRole.
Listed pay typically runs
$156,750–$215,000
across 5 roles with salary data.
As the Director of Software Engineering - Agentic AI, you will join the Applied AI Engineering team to lead the design, delivery, and scaling of production-grade AI agent capabilities. You will own the strategy for AI-enabled workflows that accelerate data modeling, pipeline generation, and data classification across a Databricks-based data platform on Amazon Web Services. Your daily responsibilities include architecting agent-driven workflows, designing secure tool-integration layers using Model Context Protocol, and establishing technical standards for Databricks workspaces, Unity Catalog, and Delta Lake. You will manage a team of engineers to build human-in-the-loop review models and automated SDLC workflows. Key technical requirements include expertise in Apache Spark, SQL Warehouses, Retrieval-Augmented Generation, multi-agent orchestration, and data governance platforms like Immuta to ensure secure, auditable, and reliable AI operations.
Define and own the Applied AI roadmap to translate business needs into production-grade data platform capabilities.
Architect and scale agent-driven workflows for data modeling, pipeline generation, and data classification.
Design a secure tool-integration layer to expose platform capabilities to agents with controlled access and auditability.
Establish technical standards for agent interactions with Databricks workspaces, Unity Catalog, and Delta Lake.
Build and manage a human-in-the-loop review model to validate and version agent outputs before production use.
Ensure the performance, scalability, and operational readiness of AI-powered pipelines through monitoring and incident readiness.
Lead the hiring, development, and management of a high-performing team of AI and data engineers.
Set governance and guardrails for AI-enabled engineering and Software Development Life Cycle automation.
What we're looking for
Formal training or certification in software engineering concepts and 10+ years of applied experience.
5+ years of experience leading technologists to manage and solve complex technical items within a domain of expertise.
Demonstrated experience leading engineering teams and owning technical roadmaps for platform capabilities used by multiple product teams.
Deep hands-on expertise with Databricks, including Unity Catalog, Delta Lake, Apache Spark, and SQL Warehouses.
Strong expertise in LLM application architecture, including RAG, tool integration, agent design patterns, and multi-agent orchestration.
Proven experience building, deploying, and operating production AI-enabled systems with engineering discipline for testing, observability, and resiliency.
Strong understanding of data governance, access control, policy enforcement platforms, and auditability expectations.
Experience designing Model Context Protocol servers or comparable tool-layer architectures (preferred).
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