Director of Software Engineering - Agentic AI

JPMorgan Chase & Co. • Columbus, OH

7h • $204,250 - $285,000

About The Position

As an Executive Director, Applied AI Engineering (Data Platform) within Corporate Technology, you will lead the design, delivery, and scaling of production-grade AI agent capabilities across a Databricks-based data platform on Amazon Web Services. You will own the strategy and technical direction for AI-enabled workflows that accelerate data modeling, pipeline generation, data classification, and governed self-service access, partnering with Information Architecture, Data Engineering, Data Governance, and business stakeholders.

This hands-on leadership role focuses on taking agentic workflows from early results to scaled, production-grade capabilities that improve the speed, quality, and governance of data product delivery. You will set direction and governance for agentic AI-enabled engineering and Software Development Life Cycle automation, establishing guardrails for validation, security, resiliency, traceability, and reuse. You will also use enterprise-authorized AI-assisted development and automation tools to improve automation outcomes and support capacity unlock initiatives at scale.

Requirements

• Formal training or certification in software engineering concepts and 10 or more years of applied experience.
• At least 5 years of experience leading technologists to manage, anticipate, and solve complex technical items within the relevant domain.
• 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, and the ability to establish secure, scalable patterns.
• Strong expertise in large language model application architecture, including retrieval-augmented generation, tool integration, agent design patterns, and multi-agent orchestration, with an emphasis on reliability and safety.
• Proven experience building, deploying, and operating production AI-enabled systems using disciplined engineering practices such as testing, observability, change management, and resiliency.
• Strong understanding of data governance and access control, including policy enforcement platforms such as Immuta or comparable technologies, and auditability expectations.
• Ability to communicate complex technical approaches as clear business value to senior stakeholders, including outcomes, trade-offs, risks, and investment needs.
• Hands-on experience using enterprise-authorized AI-assisted software development tools in the work environment for tasks such as coding, test creation, troubleshooting, or documentation, and ability to critically evaluate and validate AI-generated outputs.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and adherence to resiliency and security expectations; ability to influence leaders on safe scaling patterns and reuse.

Nice To Haves

• Experience designing and building Model Context Protocol servers or comparable secure tool-layer architectures connecting AI agents to enterprise platforms.
• Familiarity with modern data modeling approaches, such as star schema and Medallion architecture, sufficient to validate and guide AI-generated artifacts.
• Experience delivering AI capabilities in regulated industries where governance, auditability, and control requirements are central to design and operations.
• Familiarity with Sigma Computing or comparable analytics tools operating on top of Databricks.
• Experience establishing reusable agent patterns, shared semantic layers, and platform accelerators that scale across multiple teams.

Responsibilities

• Define and own the Applied AI roadmap for the data platform, translating business needs into capabilities that reduce manual effort and accelerate data product delivery.
• Architect and scale agent-driven workflows for data modeling, pipeline generation, data quality, and data classification, with clear production-readiness standards.
• Design and oversee a secure tool-integration layer, including Model Context Protocol tooling where applicable, to expose platform capabilities to agents with controlled access and strong auditability.
• Establish technical standards for agent interaction with Databricks workspaces, Unity Catalog, Delta Lake tables, and policy controls to support consistent and secure execution.
• Ensure performance, scalability, reliability, and operational readiness of AI-powered pipelines and tools, including monitoring, incident readiness, and continuous improvement mechanisms.
• Build and run a human-in-the-loop review model so agent outputs are validated, versioned, traceable, and approved through defined quality gates before production use.
• Lead delivery across concurrent workstreams, align cross-functional partners, manage dependencies, and communicate progress and risks to senior stakeholders.
• Hire, develop, and retain a high-performing team of AI engineers, data engineers, and platform specialists, fostering an inclusive culture that balances experimentation with engineering rigor.
• Set direction and governance for agentic AI-enabled engineering and Software Development Life Cycle automation within a technical area to improve speed, quality, and operational outcomes.
• Establish guardrails for validation, security, resiliency, traceability, and reuse across teams, including for release readiness controls, automated test modernization, and incident triage acceleration.
• Apply knowledge of Software Development Life Cycle tools, including enterprise-authorized AI-assisted development and automation capabilities, to improve automation value and support capacity unlock initiatives at scale.

Benefits

• Competitive total rewards package, including 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: No Education Listed